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CMSC 734 Information Visualization - Spring 2015

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

Class hours: Tues-Thurs 9:30-10:45am Room: CSIC 3118

Ben Shneiderman Office Hours: Tues Thurs 11am-noon Room: AVW 3177 Phone: 301-405-2680 Email:

Teaching Assistant: Ruth Taylor

Class Email List

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.).



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 [1] or on Amazon: [2]

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 course 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 papers, (2) critique a web-based visualization (3) use existing information visualization tools, such as Tableau, Spotfire, 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 4-5 students).

Grading: Term project (33%), Exams (16% & 20%), Application Project (8%), Homeworks (4% & 8%), Critique (4%) + Participation (7%). I also examine the performance across the semester, so one poor grade will have less impact of the final grade.

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

Class Discussion website: We will use Piazza for class discussion. It is designed for you get help fast and efficiently from classmates, the TA, and myself. I encourage you to post your questions on Piazza and tell us all about relevant websites or events:

Previous Class pages:


I appreciate the provision of:

-- Tableau data visualization software download Tableau courtesy of the Tableau for Teaching program.

-- Tableau Training videos

-- Spotfire from Tibco for use by this class, based on the long history of collaboration that goes back to the initial development of Spotfire at the University of Maryland.

Course Evaluation

Course evaluations are important and that the department and faculty take student feedback seriously. Students can go to the to complete their evaluations.

Getting started[edit]

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