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Weekly Chapter Discussions: WEEK 10 – Discussion Chapter 15 – Visual Decision Support for Policy-Making: Advancing Policy Analysis with Visualization
In the weekly Discussion tab in the course, the Professor and students interact to explore course concepts.
For full credit, you are required to post on three different days (three-time each week) and follow the guidelines for the frequency and quality provided below. For your initial post, address the four sections below, and write NO more than 500 words. Your contributions should be in your own words; quote very sparingly. Be concise. All other contributions would be a reflection of the contributions of your classmates. After your initial post, reply to the contributions by your classmates and follow the guidelines for the frequency and quality of your contributions.
- CHAPTER SUMMARY: Summarize chapter presented during the week. Identify the main point (as in “What’s your point?”), thesis, or conclusion of the key ideas presented in the chapter.
- SUPPORT: Do research outside of the book and demonstrate that you have in a very obvious way. This refers to research beyond the material presented in the textbook. Show something you have discovered from your own research. Be sure this is obvious and adds value beyond what is contained in the chapter itself.
- EVALUATION: Apply the concepts from the appropriate chapter. Hint: Be sure to use specific terms and models directly from the textbook in analyzing the material presented and include the page in the citation.
- SOURCES: Include citations with your sources. Use APA style citations and references.
and also reply to below student posts each in 100 words.
spandana-In Chapter 15, Ruppert, et al. (2015) propose a science-policy interface that is attained when information visualization is included in the policy analisy process to support collaboration between scientists and politicians. An increase in complexity if economic and societal problems presents challenges to politicians. Policy analysis is the most critical step in the process of policy-making that shiuld be approach by politicians with care. Information visualization involves the appplication of computer-supported interactive, visual representations of abatract data to amplify cognition. The primary purpose of information visualization is to support the exploration, sensemaking, and communicfation of data (Ruppert, et al., 2015). Visual decision support systems can be used to bridge gaps in policy analysis in complex societal and economic situations. Atkeholders in policy analysis include policy makers, policy analysts, modeling experts, domain experts, and politicians. Information visualizatio is an important component of the science-policy interface. It fosters communication between science and policy fields, reduces the complexity of the underlying models through abstraction of user tasks and interactions, and reduces aspects of subjectivit byb allowing stakeholders to gain access to the same information provided in an objective way via information visualization techniques.
Comai (2015) examines networkm programming as a data visualization tools that can be used when analyzing complex systems. A network diagram includes nodes and connections, which can be used in the analysis of social networks and presentation of bibliometric and intellectual property data. They are effective in showing who and how closely different stakeholders are related to a specific issue. network diagrams are a very powerful tool for visualizing cause-effect relationships between different events and can help in the anticipation of future developments. Connecting multiple event nodes helps in the visual demonstration of the cause and efffect relationship between them. This offers a broader view of the problem or issues that policy makers need to deal with.
uday-Making correct decisions a significant investigation of the issues and potential arrangements must be performed. Along these lines, leaders depend on the guidance of investigators. These examiners need to team up with outside specialists counseled as counselors. Because of various partner aptitudes the whole choice procedure may experience the ill effects of information holes. From meetings and conversations with area specialists, we distinguished three primary difficulties, portrayed as holes in the dynamic procedure. The ability in the dynamic procedure, fitness holes show up between partners with diverse information and mastery. For a collective dynamic procedure, a straightforward and unmitigated data move is required. Contingent upon the sort of the correspondence medium and the power of its utilization, there is an inactive danger of an imperfect data stream. The issue increments if information must be imparted by means of go between. At that point, extra data misfortune impacts may show up.
The investigation hole: As a moderate consequence of a dynamic procedure, elective arrangements to a given issue are made. These mind-boggling arrangements should be condensed and conveyed to the chief, who needs to choose which choice to be actualized. This bears the hazard that either the applied model isn’t abused in an ideal manner, a few outcomes are not imparted, or, surprisingly more terrible, that the model is badly characterized without an adequate approval by the included partners. The investigation of examination results by the chief would be a significant component in an effective dynamic procedure, since it would bolster normal dynamic. The emphasis hole: Subprocesses inside the choice procedure like the recreation of potential effects may not be adequately rehashed and improved by criticism circles. Just in a couple of cases, a first draft is now completely created also, functional. In addition, an iterative improvement of the examination model and consequently, its outcomes, raises the opportunity to finish up in doable arrangements. Tedious correspondence endeavors add to this hole. A crucial test in dynamic is to connect these and other information holes between partners engaged with the dynamic procedure.
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