This course examines the art, science, and practice of information visualization. Particular emphasis is placed on the ways in which position, shape, size, brightness, color, orientation, texture, and motion influence perception of information and facilitate comprehension and analysis of large and complex bodies of information. Topics include cognition and visual perception; the aesthetics of visual media; techniques for processing and manipulating information for the purpose of visualization; studies of spatial, relational, multivariate, time-series, interactive, and other visual approaches; and methods for evaluating information visualizations.

Information Visualization Syllabus (Spring 2013)

Assignments

• Weekly visualization post (30%)
• Lab report (5 x 6%)
• Final project (40%)

Topics

1. Introduction
2. History and Theory of Information Visualization
3. Perception and Visual Processing
4. Data for Visualization (Google Refine Lab)
5. Design and Narrative Structure for Visualization
6. Temporal Visualizations (Google Fusion Tables Lab)
7. Statistical Representations 1: Part-Whole, Deviation, Distribution (Tableau Lab)
8. Statistical Representations 2: Correlation, Hierarchy, Multivariate
9. Mapping and Countermapping
10. GIS & Geospatial Visualization (CartoDB Lab)
11. Relational Data & Network Analysis
12. Network Visualization (Gephi Lab)
13. Interactive Representations
14. Evaluation & Usability