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.
ITCS 4121 and 5121 are cross-listed
- ITCS 4121 - Prerequisite(s): ITSC 1213 or permission of instructor - (Catalog Entry)
- ITCS 5121 - Restriction(s): CCI graduate standing or permission of instructor (Catalog Entry)
- By University Policy, ITCS 5121 section students will have additional assignment and/or expectations.
- ITCS 5121 students are expected to have a technical background similar to the CS MS Program Admission Requirements, hence the course restriction of "CCI graduate standing or permission of instructor".
Interested students without CCI graduate standing should contact the instructor to discuss their computing background.
Syllabus: The official syllabus will be made available the first week of the semester.
Textbooks requirements may vary with instructor.
Spring 2021 - Prof. Wartell: Information Visualization: Perception for Design (Interactive Technologies) 4th Edition, Colin Ware.
The programming languages and tools may vary with instructor.
Spring 2021 - Prof. Wartell:
- General Tools:
- Programming Languages:
- Visualization Specific Tools:
- Visualization Toolkit:
Students develop several 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.
The assignments may vary with instructor.
Spring 2021 - Prof. Wartell:
- Students develop several individual programming projects plus a larger, group programming project.
- Students are also evaluated on reading and lecture material.
- One or more graded tutorials covering the General Tools (listed above) may be assigned early in the semester. Students with sufficient, documented prior experience will be allowed to opt. out of some of the tutorials.
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.
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