Innovations in Visualization

Information Visualization

CPSC 583, Fall 2010

Information visualization is a computer science research area that is involved with developing and investigating interactive visualizations that are specifically created to help people gain a better understanding of abstract data. Through careful analysis of data, creation of visual representations, and implementation of these representations with meaningful interaction techniques, information visualization researchers create interactive visualizations to increase our ability to gain insight and make decisions for many types of datasets, tasks, and analysis scenarios.

Lecture: Mondays and Wednesdays 10:00 to 11:15, MS 156

Tutorial: Mondays and Wednesdays 11:30 to 12:45, MS 156

Office Hours: Mondays and Wednesdays 12:45 to 1:45, MS 680J

Prerequisites: CPSC 319 or 331; Prior or concurrent completion of CPSC 453 or 481 is strongly recommended.

Course Overview:

This will be a hands on course where students will be involved with understanding, assessing, and implementing information visualizations. The format will include lectures, discussion, presentations, and readings. Relevant topics will be chosen to enable students to create comprehensible interactive visualizations and may include:

  • Representation (developing mappings from data to visual structures).
  • Interaction (queries, navigation, visual cues).
  • Screen real estate; how to make best use of available presentation space.
  • Emphasis graphics; use of various techniques to great emphasis, focus, clarity.
  • Applications. Text, web, information workspaces, biological, ecological, social data, etc.
  • Variations in information dimensionality (1D, 1D+, 2D, 2D+, 3D, Multi-D).
  • Previous research in information visualization. (Playfair, Bertin, Tufte, Tukey)
  • Perception. A current research direction is to base information visualization on our perceptual abilities. We will examine this idea in terms of future directions and current practices.
  • Visual literacy. Communication theory - process vs. semiotic; Learning theory – reversibility, interactivity, externalization, Visual Language
  • Considering variations in intention: for whom – education, communication, research; to show – spatially explicit data, abstract data, process data.
  • Evaluation issues.

Course Details

check this page for course notes, assignments, etc.

Recommended Books

Information Visualization: Design for Interaction (2nd Edition)
Robert Spence, Prentice Hall.

Visualizing Data
Ben Fry, O'Reilly

Additional Books

Information Visualization

Information Visualization: Perception for Design
Colin Ware, Morgan Kaufmann.

Readings in Information Visualization: Using Vision to Think
Stuart K. Card, Jock Mackinlay, Ben Shneiderman (editors), Morgan Kaufmann.

Visual Thinking for Design
Colin Ware, Morgan Kaufmann.

Beautiful Visualization: Looking at Data through the Eyes of Experts
Julie Steele and Noah Iliinsky, O'Reilly Media.

Data Flow: Visualising Information in Graphic Design (2 Books)
R. Klanten, N. Bourquin, S. Ehmann, F. van Heerden, Die Gestalten Verlag.


Learning Processing: A Beginner's Guide to Programming Images, Animation, and Interaction
Daniel Shiffman, Morgan Kaufmann.

Processing for Visual Artists: How to Create Expressive Images and Interactive Art
Andrew S. Glassner, A K Peters.

Getting started with Processing
Casey Reas and Ben Fry, O'Reilly Media.

Information Visualization Prototyping Tools:

  • Processing (will be used for course project)
  • Prefuse: Information Visualization framework for the Java programming language.
  • Flare: ActionScript 3 libraries for interactive visualizations on the web.
  • InfoVis Toolkit

Interesting Information Visualization Resources:

Blogs featuring information visualization:

Information on various aspects around information visualization:InfoVis Wiki

Interesting InfoVis systems:


Information Visualization Tools:

Information Visualization Research here at the INNOVIS Lab: