Assignment 1: Research Sources - AU ENG102 - Use attachments for reference

Arzberger, P., Schroeder, P., Beaulieu, A., Bowker, G., Casey, K., Laaksonen, L., ... & Wouters, P. (2004). Promoting access to public research data for scientific, economic, and social development. Data Science Journal, 3, 135-152.

The source provides access to sharing of the data which is deemed to be very important for the conduct as well as scientific advancement. This sources, therefore, provides an argument that the research data which is funded publicly ought to be openly available to the maximum extent possible. In this regards, the source denotes that in order to seize upon advancement of the cyber infrastructure as well as the explosion of data in a range of scientific disciplines. This ensures easy access and sharing of the data which is publicly funded and beyond the technological solutions.

Janssen, M., Charalabidis, Y., & Zuiderwijk, A. (2012). Benefits, adoption barriers, and myths of open data and open government. Information systems management, 29(4), 258-268.

This source is based mainly on the data collected through various interviews and therefore highlights various benefits attributed to open data. The source also suggests that a conceptually simplistic view in most cases is adopted pertaining to the open data which relates automatically to the data uses as well as its benefits. The source, in addition, presents the five myths linked to the open data which in essence place expectations within the realistic perspective. The source also recommends the activities which should be done by the organization in utilizing the big data.

Janssen, M., Konopnicki, D., Snowdon, J. L., & Ojo, A. (2017). Driving public sector innovation using big and open linked data (BOLD). Information Systems Frontiers, 19(2), 189-195.

This book denotes that innovation in the government pertains to finding new techniques on improving the society and the government itself with the relationship which exists between the government and the public. The source goes on to explain that the data-driven innovations will lead to dramatic transformations of the public sectors which in essence can create societal benefits like little or no pollution and the fewer traffic jams in the city. In essence, the big and open data as explained by the article denotes that it plays a pivotal role in the transformational as well as collection and combination as well as sharing of the data from various sources.

Jetzek, T., Avital, M., & Bjørn-Andersen, N. (2013). Generating value from open government data.

This source denotes that driving force for the changes in the society as well as the trends towards the open government data which is being discussed mainly by the stakeholders and the other public bodies. In essence, the conceptual model has been developed on the way the data and the resources ought to be transformed to the value. This as well denotes the casual relationships which exist between the contextual and the enabling factors for the organization's values. This thus shows that mainly the resource governance and the societal capabilities which stimulate the generation on the social, economic values complement the openness.

Kapoor, K., Weerakkody, V., & Sivarajah, U. (2015, October). Open data platforms and their usability: Proposing a framework for evaluating citizen intentions. In Conference on e-Business, e-Services and e-Society (pp. 261-271). Springer, Cham.

This book denotes that the government bodies come across the release of public data so that transparency can be increased especially on the public services and most importantly in enticing the citizens to participare in the policy-making processes. The book further explains the channels which are used in making the open data to be available to the citizens which bring together data which relates to the public services for the public to get aware easily. In essence, the author examines the usability issue relating to the open data platforms and most importantly proposes the methods which can be used in evaluating the usability.

Kitchin, R. (2014). The data revolution: Big data, open data, data infrastructures, and their consequences. Sage.

This source provides guidance pertaining to the essentials of a data and what is being done currently as well as what was done in the past. This is to say that the source provides ramifications on the big and open data information systems. The sources additionally provide a step to step explanation on the complete overhaul of the data while considering various factors such as the geo data in-depth and fewer data as utilized in the organizations. In essence, the source provides beneficial information and guidelines which can help one to understand more pertaining to the public sector big data.

Ohlhorst, F. J. (2012). Big data analytics: turning big data into big money. John Wiley & Sons.

This book provides unique insights to implement the big data and most importantly reap big returns by focusing on the business as well as the financial values of the big data. This book additionally demonstrates the importance of data analytics and defines the various processes as well as the tangible and intangible values pertaining to the big data. The book as well reveals the big data analytics being the next wave for the business which is looking to become competitive and thus provides the analytics of the data and leverage on the key elements of the organization to grow.

Zillner, S., Oberkampf, H., Bretschneider, C., Zaveri, A., Faix, W., & Neururer, S. (2014, August). Towards a technology roadmap for big data applications in the healthcare domain. In 2014 IEEE International Conference on Information Reuse and Integration (IRI) (pp. 291-296). IEEE.

This source explains that big data technologies are mainly used in the improvement of quality as well as efficiency in healthcare delivery and any other organizational performance. It further denotes that the applications of the big data include the clinical operations, financial as well as outcome data. To enable seamless access to the data as well as other technical requirements which include the digitalization and the semantic annotation, the source shows that the privacy and security of the data ought to be maintained. The book thus introduces detailed results and analysis of technical roadmap for big data in organizations.