Innovations in Visualization

Information Visualization

CPSC 599.28/601.28

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.

Winter 2008, Tuesdays and Thursdays 9:30 to 10:45
Location: MS 680A

Prerequisites: CPSC student in good standing or permission of the department. Courses in graphics (CPSC 453) and/or human-computer interaction (CPSC 481) are an asset but are not required.

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 (devloping 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.

Information Visualization Research here at the INNOVIS Lab:

Information Visualization Tools:

Information Visualization Prototyping Tools:

Interesting Information Visualization Resources: