Information Visualization and Aesthetics

Maureen Stone and Polle Zellweger, Information School, University of Washington

email: stone[at]stonesc.com, pzellweger[at]acm.org

Homepage of author: http://www.stonesc.com/

Homepage of course: http://courses.washington.edu/info424/


Title of course: Information Visualization and Aesthetics

Aimed at what category of students: Students of Information

Objectives of the course:

This course describes the key design principles and techniques used in visualizing information, together with the perceptual principles that support them. It is structured to provide both concrete experience with real data and tools as well as a broad view of the rich world of information visualization. Students will learn both how to design and how to explore, analyze and evaluate. By the end of this course, students will be able to:
1) Describe the key design guidelines and techniques used for the visual display of information, including their relationship to human perception,
2) Design interactive visualizations to support human activities, using real data and a user-centered process,
3) Explore and critically evaluate a wide range of visualization techniques and applications.

 

List topics of course:

  • Fundamental principles for graphical excellence and integrity, primarily those articulated by Tufte and Few, but including also those articulated by Ben Shneiderman and others from the interactive visualization community.
  • Understanding data with respect to the different tasks and visualization methods it supports.
  • Real world data, which includes outliers, missing values, and may need reorganizing and transforming to be visualized effectively.
  • An overview of the visual and perceptual principles relevant to visualization
  • Few’s specific rules and techniques for clearly communicating the information encoded in numeric data.
  • Techniques for managing complexity: Overview plus detail, small multiples, animation, layering
  • The perception and application of grayscale and color to label, layer and to control attention, including visual accessibility issues.
  • Visualization methods using maps
  • Visualization methods for trees and networks
  • Interaction methods for control, selection and navigation
  • Usability and evaluation

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