Main Page

From Cmsc734_08
Jump to: navigation, search

CMSC 734 Information Visualization - Spring 2008

 Dept of Computer Science, University of Maryland
 Prof. Ben Shneiderman

Consult the User's Guide for information on using the wiki software.

Class hours: Tues & Thurs 11:00am - 12:15pm Room: CSIC 3118

Office hours: Tues & Thurs 10:00am-11:00am Room: AVW 3177 Phone: 301-405-2680 Email:

Syllabus with course schedule


Project Ideas

Please post project proposals on the wiki, with descriptive title, team member names, outside client/sponsors, and a project description, plus relevant references (papers, websites, etc.).


--> April 15 Discussion-2D-3D
--> April 22 Discussion-Color

Topics: What is information visualization? How is it related to scientific visualization? How does it combine with data mining? Information visualization is emerging as an important fusion of graphics, scientific visualization, database, and human-computer interaction. Dozens of innovative visualizations for 1-, 2-, 3-, and multi-dimensional data have been proposed, along with creative designs for temporal, hierarchical, and network data. This seminar will examine the design alternatives (overviews, dynamic queries, zooming, etc.), algorithms and data structures, coordinated views, plus human factors evaluations of efficacy for a variety of tasks and users.

Students will read current literature and conduct collaborative projects to design, implement, and/or evaluate existing or novel visualizations. Mid-term and final exams will be given, so the course qualifies for MS and PhD comps.

Homework: Students will (1) read, present and critique papers (pairs of students), (2) critique a web-based visualization (individual) (3) use existing information visualization tools, such as Spotfire, Tableau, TimeSearcher, HCE, and Treemap to build useful visualizations on data sets (pairs of students), (4) conduct a major team project to create or extend an information visualization to deal with a realistic problem, and conduct case study evaluations (teams of 3-5 students).

Grading: Term project (35%), Exams (18% & 22%), Homeworks & Participation (25%)

Readings: Key papers will be assigned for reading, including chapters of "Illuminating the Path: The Research and Development Agenda for Visual Analytics" Other sources include:

1) Designing the User Interface, 4th Edition, B. Shneiderman & C. Plaisant, Addison Wesley (2005).   Chapter 14.
2) Readings In Information Visualization: Using Vision to Think,
      Stuart K. Card, Jock D. Mackinlay, and Ben Shneiderman,
      Morgan Kaufmann Publishers, San Francisco, January 1999, 686 pages, ISBN 1-55860-533-9, 

Previous Class pages:

Getting started