CMSC 734 Information Visualization - Spring 2011
Dept of Computer Science, University of Maryland Prof. Ben Shneiderman Teaching Assistant: Gleneesha Johnson
Consult the User's Guide for information on using the wiki software.
Class hours: Wednesday 4:00pm - 6:30pm Room: CSIC 1121
Ben Shneiderman Office hours: Wed 2-4pm Room: AVW 3177 Phone: 301-405-2680 Email: firstname.lastname@example.org
Gleneesha Johnson Office Hours: Tues 2-4pm Room AVW 4160 Email: email@example.com
Syllabus with course schedule
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.).
- Homework #1 New York Times Visualization Critique
- Homework #2 ManyEyes Application Report
- Homework #3 NodeXL Application Report
- Application Projects
- Term Projects Sign up for Critiques
Books: Hansen, M., Shneiderman, B, and Smith, M. A., Analyzing Social Media Networks with NodeXL: Insights from a Connected World, Morgan Kaufmann Publishers (2011). ISBN: 9780123822291. Available from Campus Bookstore, or  or on Amazon: 
Keim, D., Kohlhammer, J., Ellis, G., and Mansmann, G. (Editors), Mastering the Information Age: Solving Problems with Visual Analytics, Eurographics Association, Goslar, Germany (2010). Available as free download (25MB, 175 pages).
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, apply, 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, Treemap, LifeLines2, and NodeXL to build useful visualizations on data sets (pairs of students), (4) conduct a major team project to create, extend, or apply an information visualization tool to deal with a realistic problem, and conduct case study evaluations (teams of 3-5 students).
Grading: Term project (35%), Exams (17% & 21%), Homeworks & Participation (27%)
Readings: Key papers will be assigned for reading, including chapters of "Illuminating the Path: The Research and Development Agenda for Visual Analytics" http://nvac.pnl.gov/agenda.stm Other sources include:
1) Designing the User Interface, 5th Edition, B. Shneiderman & C. Plaisant, Addison Wesley (2010). http://www.aw-bc.com/dtui Chapter 14. Two sample chapters at http://www.pearsonhighered.com/dtui5einfo/ 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, http://books.elsevier.com/us/mk/us/subindex.asp?isbn=9781558605336
Previous Class pages:
Other University Class pages:
Berkeley iSchool: http://courses.ischool.berkeley.edu/i247/s08/projects.html
I appreciate the provision of:
-- Tableau's data visualization software courtesy of the Tableau for Teaching program.