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: firstname.lastname@example.org
Teaching Assistant: Ruth Taylor 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 Interactive Information Visualization Critique
- Application Projects
- Homework #2 NodeXL Application Report
- Term Projects Sign up for Critiques -- Read Grading Criteria for Term Projects
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 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" http://nvac.pnl.gov/agenda.stm
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: https://piazza.com/umd/spring2015/cmsc734/home
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Course evaluations are important and that the department and faculty take student feedback seriously. Students can go to the www.courseevalum.umd.edu to complete their evaluations.
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