THERE WAS NO OFFICIAL SITE THAT PROVIDED A
WAY FOR THE PUBLIC TO INTERROGATE THE DATA
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements. The time period ‘information journalism’ can cover quite a
number disciplines and is used in varying ways in information organizations, so it is able to be
useful to define what we mean by ‘statistics journalism’ at the BBC. Broadly the term covers
projects that use data to do one or more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
The time period ‘information journalism’ can cover quite a number disciplines and is used in
varying ways in information organizations, so it is able to be useful to define what we mean by
‘statistics journalism’ at the BBC. Broadly the term covers projects that use data to do one or
more of the following:
Allow a reader to discover information that is individually applicable.
Reveal a story that is super and previously unknown.
Assist the reader to better understand a complex issue.
These categories can also overlap and in a web environment can often benefit from some level
of visualization.
Make It Personal
On the BBC news website, we have been using data to provide services and tools for our users
for well over a decade. The most consistent example, which we first published in 1999, is our
school league tables, which use the statistics published annually by the government. Readers
can find local schools by entering a postcode, and compare them on a number of indicators.
Education journalists also work with the development team to trawl the data for stories in
advance of publication.
When we started to do this, there was no official site that provided a way for the public to
interrogate the data. However, now that the department for education has its own similar
service, our offering has shifted to focus more on the stories emerging from the data.
The challenge in this area should be to provide access to data where there is a clear public
interest. A recent example of a project where we exposed a large dataset not normally available
to the wider public was the unique report on every death on every road. We provided a
postcode search allowing users to find the location of all street fatalities in the UK in the past
decade.
We visualized some of the primary data and figures emerging from the police statistics and, to
give the project a more dynamic feel and a human face, we teamed up with the London
Ambulance Association and BBC London radio and television to track crashes across the
capital as they took place. This was reported live online, as well as through Twitter using the
hashtag #crash24, and the collisions were mapped as they were reported.
Simple Tools
As well as providing ways to explore large data sets, we have also had success creating simple
tools for users that offer individually relevant snippets of data. These tools appeal to the time-
poor who might not choose to explore lengthy analysis. The ability to easily share a ‘personal’
fact is something we have started to incorporate as standard.
A light-hearted example of this approach is our feature "The World at 7 Billion: What’s Your
Number?" published to coincide with the official date at which the world’s population passed 7
billion. By entering their birth date, the user could find out what ‘number’ they were, in terms of
the global population, when they were born and then share that number through Twitter or
Facebook. The application used data provided by the UN Population Development Fund. It was
very popular and became the most shared link on Facebook in the UK in 2011.
Another recent example is the BBC Budget Calculator which enabled users to find out how
better or worse off they might be when the Chancellor’s budget takes effect — and then share
that figure. We teamed up with the accountancy firm KPMG LLP, who provided us with
calculations based on the annual budget, and then we worked hard to create an engaging
interface that would encourage users to complete the task.
Mining The Data
But where is the journalism in all this? Finding stories in data is a more traditional definition of
data journalism. Is there a gem buried within the database? Are the figures accurate? Do they
prove or disprove an issue? These are all questions a data journalist or computer-assisted
reporter should ask themselves. But a great deal of time can be taken up sifting through a large
data set in the hope of finding something remarkable.
In this area, we have found it most efficient to partner with investigative teams or programs that
have the expertise and time to analyze a story. The BBC current affairs program Panorama
spent months working with the Centre for Investigative Journalism, collecting data on public
sector pay. The result was a TV documentary and online the special report "Public Sector Pay:
The Numbers" where all the data was published and visualized with zone-by-zone analysis.
As well as partnering with investigative journalists, having access to numerate reporters with
specialist expertise is crucial. When a business colleague at the team analyzed the spending
review cuts data put out by the government, he came to the conclusion that it was making them
sound bigger than they actually were. The result was an exclusive story, "Making Sense of the
Data," complemented by a clear visualization which won a Royal Statistical Society award.
Understanding An Issue
But data journalism doesn’t have to be an exclusive no-one else has spotted. The job of the
data visualization team is to combine great design with a clear editorial narrative to provide a
compelling experience for the user.
Engaging visualizations of the right data can be used to provide a better understanding of an
issue or story and we often use this approach in our storytelling on the BBC. Heat-mapping data
over time to give clear view of change is one method used here in our UK Claimant Count
Tracker.
The data feature "Eurozone Debt Net" explores the tangled web of intra-country lending. It helps
to explain a complex issue in a visual way, using color and proportional arrows combined with
clear text. An essential consideration is to encourage the user to explore the feature or follow a
narrative, and never feel overwhelmed by the numbers.
Team Overview
The team that produces data journalism for the BBC News website is built from approximately
20 journalists, designers, and developers. As well as data projects and visualizations, the team
produces all the infographics and interactive multimedia features on the news website. Together
these form a suite of storytelling techniques we have come to call ‘visual journalism’. We don’t
have individuals who are specifically identified as ‘data’ reporters, but all editorial staff on the
team must be proficient at using basic spreadsheet applications such as Excel and Google
Docs to analyze data.
Central to any data projects are the technical skills and guidance of our developers and the
visualization skills of our designers. While we are all either a journalist, designer, or developer
‘first’, we continue to work hard to increase our knowledge and proficiency in each other’s areas
of expertise.
The core products for interrogating data are Excel, Google Docs, and Fusion Tables. The team
has also, but to a lesser extent, used MySQL and Access databases and Solr for interrogating
larger data sets and used RDF and SPARQL to begin looking at ways in which we can model
events using linked data technologies. Developers will also use their programming language of
choice, whether that’s ActionScript, Python, or Perl, to manipulate, parse, or generally pick apart
a dataset we might be working on. Perl is used for some of the publishing.
We use Google and Bing Maps and Google Earth along with Esri’s ArcMAP for exploring and
visualizing geographical data.
For graphics, we use the Adobe Suite including After Effects, Illustrator, Photoshop, and Flash,
although we would rarely publish Flash files on the site these days as JavaScript, especially
JQuery and other JavaScript libraries like Highcharts, Raphael, and D3 increasingly meet our
data visualization requirements.
