Information Visualization is a discipline of computer science that develops interactive applications for exploring data. Whereas scientific visualization visualizes data with inherent 3D geometric structure, information visualization typically visualizes more abstract data sets stored as tables, networks, hierarchies, or text. This course covers information visualization concepts, theories, design principles, popular techniques, evaluation methods, and information visualization applications.
All required reading will come from a reading list of roughly 15 journal and conference papers.
Students develop 1 or 2 individual, small programming projects plus a major group programming project. Students are evaluated on reading material using either Clicker based quizzes or short written summaries. Students also will make several presentations including “design contests” where students design (but do not implement) a visualization to explore one of several data sets.
Matthew Ward, Georges Grinstein, and Daniel Keim. Interactive Data Visualization – Foundations, techniques, and applications. A K Peters, 2010
Colin Ware. Information Visualization: Perception for Design (2nd Edition). Morgan-Kaufmann, 2004.
Edward Tufte. The Visual Display of Quantitative Information (2nd Edition). Graphics Press, 2001.
Edward Tufte. Envisioning Information. Graphics Press, 1990.
Edward Tufte. Visual Explanations: Images and Quantities, Evidence and Narrative. Graphics Press, 1997.