G22.3033-010: Information Visualization

Instructor: Brook Conner

A graduate-level course introducing information visualization and surveying the state of the art.

This course will introduce the cross-disciplinary field of information visualization: the process of creating pictures from data as an aid for human comprehension and decision-making. Bar graphs are a simple example of a visualization; this course will move well beyond that into scientific data, multivariate and time-varying information, and complex, abstract data structures. Information visualizations are often not simple, two-dimensional static pictures, so the course will deal with the role of animation and direct manipulation, methods of handling extremely large data sets of arbitrary dimension, and tools for filtering data to provide useful subsets. As the goal of a successful information visualization is to aid human thought, all of these approaches will be presented in the context of an understanding of human perceptual and cognitive processes.

The Course

Logistics

When and where

The course meets once a week, Mondays, from 7pm to 9pm. The location will go on this page shortly.

Reaching the instructor

The instructor's office hours are immediately prior, or by appointment.

You may contact him by e-mail either as conner@cs.nyu.edu or me@nellardo.com.

Course Work

Readings

Primarily papers from current scientific literature (journal papers, conference proceedings). In addition to the bulk of the required text (which is itself conference and journal reprints), expect to receive URLs or copies for additional reading.

Written assignments

Expect five written assignments during the course. Each should be approximately the length of a short conference submission, e.g., 10-20pp of manuscript, plus references and figures. Tentative topics are as follows:

  • A survey of 2D visualizations. Provide an organizing principle for the survey (e.g., a taxonomy). Discuss their various costs and benefits. Identify one ineffective visualization in wide use (e.g., over-decorated bar graphs in USA Today) and one effective visualization that is under-used.
  • A survey of 3D, animated, and interactive visualizations. Again, organize the survey in a useful way. Discuss their costs and benefits. Explain how these kinds of visualizations are or are not in widespread use.
  • A specification of a particular visualization in a practical context. This is the first stage of the final programming project, which may be done in small teams (less than five) if desired. Thus, the specification may be written jointly by the team planning the implementation. The team should be prepared to present this specification to the class.
  • A design document for the visualization project. Again, this may be written by a team, and the team should be prepared to present the design to the class.
  • A final paper discussing the visualization and its implementation. In addition to the paper, the team should be prepared to demonstrate their application to the class and briefly present the interesting features of the visualization and its implementation.

Programming project

Towards the end of the course, out-of-class work will focus on an implementation of a visualization technique in a practical setting. An excellent project will be robust and useful enough to consider releasing as open source (i.e., if the instructor can use it without it crashing and without the hovering attention of the implementation team).

These projects will be discussed in detail by the class (see writing assignments above). If desired, students can work on them in small teams (no more than four)., though this is not required.

Prerequisites

Required

Substantial background in any one of:

  • Cognitive or perceptual science
  • Computational Geometry
  • Computer graphics
  • Graphic or media design
  • Scientific visualization

Recommended

Substantial background in two or more of the above topics. "Substantial background" is taken to mean a graduate-level course in the subject or substantial undergraduate work (i.e., degree major).

Texts

Primary Text

Readings in Information Visualization , Card, Mackinlay, Shneiderman, eds. and authors. Morgan Kaufman, 1999.

Secondary Texts

The Visual Display of Quantitative Information ; Envisioning Information ; Visual Explanations , all Edward Tufte. Graphics Press. Especially recommended for students with little background in graphic or user interface design.

Computer Graphics: Principles and Practice (2nd edition or newer), James Foley, Andries van Dam, Steven Feiner, John Hughes. Addison Wesley, 1992. Recommended for students with little experience in graphics algorithms. If you don't know how the pictures get on the screen, this is the book to read.

Computational Geometry , Preparata and Shamos. Morgan Kaufman, 1991. Recommended when you want the algorithm to arrange the things you put on the screen. Foley/van Dam draws it, Preparata/Shamos figures out how to arrange it, and Tufte figures out what to draw in the first place.