IEC7
Discussion-1 with 100 words.
Among the various categories of tools used in policy making, I have chosen to pic visualization and argumentation. I will begin by discussing data visualization category. Data visualization entails a graphical display of information which is usually for two purposes; the first is to make sense to the audience and the other for communication. Data visualization is a dominant measure by which is used to determine and cognize the stories and then go ahead and represent it in front of people. Data visualization could be used to come up with a graphical representation of the ways anticipated to improve the timetable for train transportation. By this, I mean that getting this information could help calculated and determine the best times that the train or bus could depart or take in passengers. Comparing the departure time that has the highest number of people with the working hours could be of great aid (Cotreras W., 2019).
The other category is argumentation. Truthfully, individuals normally have numerous ways to consult with their representatives about things like policy proposals, justification seeking, objecting to maybe all or part of something or lastly making counter-proposals. The first thing that is usually done is making the statement of justification. After that, the representatives usually need to be made to understand the objections and they are always inquisitive about it. The next thing that is typically expected by the representatives is a well put down proposal which would also tend to woe them into accepting the requirements of the policy to be formulated. With these, the citizens could argue out their points and explain the best times schedules, and they will include the ones they have gotten from data visualization (Wardeh M., Wyner A., Atkinson K., & Capon, T. B., 2013).
References:
Cotreras W. (2019, January 25). How data visualization enhances business decision making. Retrieved from https://www.widerfunnel.com/data-visualization-examples/
Wardeh M., Wyner A., Atkinson K., & Capon, T. B. (2013). Argumentation based tools for policy-making. Retrieved from https://dl.acm.org/citation.cfm?id=2514640
Discussion-2 with 100 words.
It is always better for the Smart City if their Local transportation is always on time, uses less energy and is less pollutant so that it could serve the passengers better while taking care of the environment. For optimizing bus and local train schedules to minimize energy use and passenger wait times in a Smart City environment the two most important tools for the development of the policy are:
1. Visualization: As the scheduling of the train and bus requires a lot of data to be considered hence visualization of the data will help in this. It helps the data makers to view the huge piled data in a go; it organizes the data in a way that helps in identifying the trends and also helps in directing the graphs of the decision. It will help the decision makers to get the view of the possible connections among the schedules of the buses and trains with the timings of the local passenger. This tool helps in quickly accessing the data and so it will directly minimize the use of energy and will also reduce the waiting time of the passengers (Hagen, Keller, Yerden & Luna-Reyes, 2019).
2. Big data analytics: This tool of decision making will help in managing and handling the big data as the schedules of buses and trains are comprised of big data. This decision making tool helps in digging out the solution in the real-time, which is he most required thing in the given situation. It also helps in increasing the capacity without any additional investment to be made (Elgendy & Elragal, 2016).
References
Elgendy, N., & Elragal, A. (2016). Big Data Analytics in Support of the Decision Making Process. Procedia Computer Science, 100, 1071-1084. doi: 10.1016/j.procs.2016.09.251
Hagen, L., Keller, T., Yerden, X., & Luna-Reyes, L. (2019). Open data visualizations and analytics as tools for policy-making. Government Information Quarterly, 101387. doi: 10.1016/j.giq.2019.06.004
Discussion-3 with 100 words.
Several tools have been mentioned in chapter 7 that seems to be so crucial in the policymaking process. The technological sector has advanced significantly in the business, which has also made it essential to incorporate the concepts of technology tools in policymaking. The two main tools that have been covered in the chapter are visualization tools and the opinion mining tools. These two tools have significant implications in general policymaking, which means they can play a central role in optimizing bus and local train schedules (Raisinghani, Bekele, Idemudia & Nakarmi, 2016).
The visualization tools will help the project team to try coming up with an incorporative structure of how the project should work. This policy is meant to help optimize the operation of the bus by minimizing the energy and the passenger's waiting duration. This tool helps in making policy projections and how it is supposed to work. The device will involve the use of technologies like Data-place and Gap-minder. This will be useful in designing the general data requirement and how they are expected to work in the Smart City environment. This policy will outline the exact waiting time and ensure that the business is well planned to arrive at the right time to ensure that the audience does not over wait.
The other tool that was discussed in the chapter is the opinion mining tool. This will be focusing on deriving a variety of opinions about the policy content from the different sources available. This program is quite large, and it will involve the use of quite several stakeholders, this strategy that will help mine the relevant data from the stakeholders (Raisinghani, Bekele, Idemudia & Nakarmi, 2016).
In conclusion, this chapter has covered quite several tools that are necessary for technological policymaking. This chapter has discussed the way they can exploit the technology to build an efficient policy in the Smart City environment.
References
Raisinghani, M. S., Bekele, R., Idemudia, E. C., & Nakarmi, A. (2016). Managing Knowledge in Organizations: Tools & Techniques for competitive advantage. Journal of Business Management. 32(2). 45-67.