Reviewing Information Visualization Tools

Problem
A great deal of the information we encounter every day can be considered multivariate data, that is, data which has any number of dimensions or fields. For example, consider data about feature motion pictures. Each film can have a number of pertinent dimensions of information such as its type (comedy, drama, sci-fi), its director, the amount of money it made, its length, its actors, etc. It's possible to think of similar features for things like stocks, automobiles, baseball players, items sold at a store, and so on.

People use information like this as they face decisions every day in their lives. Furthermore, managers and business people need access to this kind of data as they decide the directions of their companies.

One way to help people understand this kind of information is to present it in more informative, visual manners. This is the idea behind the relatively new field of Information Visualization. Researchers in Information Visualization have developed a number of innovative techniques and systems for communicating large multivariate data sets. In fact, these research efforts have even blossomed into start-up companies offering services to businesses as decision-making aids.

The purpose of this project is for you to learn more about the field of information visualization, to acquire hands-on experience using the visualization tools, and to do a comparison of the tools. First, read the articles below to learn a little about the field. Next, go to the Web sites for the companies Visible Decisions (www.vdi.com), Spotfire (www.spotfire.com), Inxight (www.inxight.com), and Visual Insights (www.visualinsights.com), and download the SeeIt, Spotfire, Table Lens and Advizor systems respectively. Run through the demos and tutorials that each provides. (Do your best trying out the systems. We're hoping to get a version of them on the Windows NT cluster here too. Please check with Prof. Stasko to learn about their availability.)

Background
Read the following four articles to learn more about this field.

• Card, S., Mackinlay, J. and Shneiderman, B., Readings in Information Visualization, Using Visualization to Think, Morgan Kaufmann, 1999, pp. 1-31.
• Rao, R. and Card, S., "The Table Lens: Merging Graphical and Symbolic Representations in an Interactive Focus+Context Visualization for Tabluar Information", Proceedings of the SIGCHI '94 Conference, pp. 318-322.
• "IVEE: An Information Visualization and Exploration Environment", C. Ahlberg and E. Wistrand, Proc. of Information Visualization '95 Conference, Oct. 1995, pp. 66-73. (Also have Spotfire documentation.)
• Wright, William, "Information Animation Applications in the Capital Markets," Proceedings of the Information Visualization '95 Conference," Atlanta, GA, Oct. 1995, pp. 19-25. (Also have other VDI promotional materials.)
• Eick, S., "Advizor: A Technical Overview", unpublished article.

For more background about the field of information visualization, check out this Fall's course on that topic, CS 7450, www.cc.gatech.edu/classes/AY2000/cs7450_fall/.

Deliverables
You should turn in a report (5+ pages) that reviews what you have learned in the project and your impressions of Information Visualization. Most importantly, the report should compare and contrast the different systems that you used. What did you like and dislike about each? What were the relative strengths and weaknesses of each? What visualizations did they provide? What were their user interfaces like? Feel free to include some screenshots to support your opinions.

Evaluation
You will be evaluated on the quality of your report overall, primarily the depth and throughfulness of your analysis of the different visualization tools. Don't just review what they do. Provide a good subjective analysis of their strengths and weaknesses.