Information Visualization
Page Limit: 4 pages max (double-spaced).
This is an open-book exam. Answer any two of the three questionslisted below. Submit all your answers in a document file under the Assignment page on Blackboard.
You may draw upon your own learning through the reading materials, software experiences, and in-class discussions of this course as well as relevant materials on the Internet, provided that proper references are included accordingly.
Question 1
Explain Fundamental Principles of Information Visualization
Reflect on the lectures, software experience, and other learning materials that you have studied in our course so far, explain the following fundamental principles and their practical implications:
1. Explain why mental models may be biased, inaccurate, or even completely wrong as a representation of a situation, i.e. as a story of what is going on with reference to available information or data.
2. Explain steps that can be taken to reduce the risk of generating a wrong mental model.
Question 2
A communicative network represents relations between people in terms of the extent to which they communicate with one another.
1. In your own words, explain the concept of a structural hole in such networks.
2. Given that Person A has the highest degree centrality (i.e., the highest number of relations with others in the network) and Person B has the highest betweenness centrality (i.e., the highest number of shortest paths from all people to all others that pass through Person B in the network), which of them,in theory, is more likely to be able to come up with good ideas in the relevant context of the underlying network? Explain and justify your reasoning.
Question 3
Reflect on the three homework projects of your own, i.e. Projects A, B, and C, describe one example from each project in terms of the 7-task by 7-data type taxonomy.
1. Project A: one example of information visualization with RAW
2. Project B: one example of information visualization with Tableau
3. Project C: one example of information visualization with CiteSpace or VOSviewer