CMSC 436/636: 
Data Visualization

Computer Science and Electrical Engineering Department 
University of Maryland Baltimore County

Autumn 2011

Time: MW 2:30-3:45  ITE 231

Instructor:

Dr. Penny Rheingans, 355 / 452 ITE, rheingan AT cs.umbc.edu, Phone:(410)455-3554 / 2809

Office Hours: Mon. 1-2:30pm in ITE 355

Description: 
This course will cover topics in visualization: the visual representation of large amounts of data. The format for the course will include group discussions of papers, lectures by the instructor, and student presentations of papers. The grading will be based on participation in class, critical assignments, and group class projects. Projects have the potential of leading to work that forms the basis of an Undergraduate Honors Thesis, Master's project, or Ph.D. research topic. A partial list of topics includes the following:

Tentative Schedule

Readings: Students will read and discuss seminal and current technical research papers. A list of readings (in progress and subject to frequent update) is available here .

Assignments:

Grades: Grades will be assigned on the basis of construction of visualizations (20%), critical reviews of published visualizations (5%), discussions and reviews of technical papers (15%), and class project (60%).
Academic Honesty By enrolling in this course, each student assumes the responsibilities of an active participant in UMBC's scholarly community, in which everyone's academic work and behavior are held to the highest standards of honesty. Cheating, fabrication, plagiarism, and helping others to commit these acts are all forms of academic dishonesty, and they are wrong. Academic misconduct could result in disciplinary action that may include, but is not limited to, suspension or dismissal. To read the full Student Academic Conduct Policy, consult the UMBC Student Handbook, the Faculty Handbook, or the UMBC Policies section of the UMBC Directory. [Statement adopted by UMBC's Undergraduate Council and Provost's Office.]

Cheating in any form will not be tolerated. In particular, plagiarism of any published work, another student's work, or your own previously published or submitted work without proper attribution will not be tolerated. If you have any questions about what is acceptable, please bring them to me before submitting your work. The minimum penalty for a violation of the academic honesty policy is a zero on the assignment. Other penalties may include a letter grade reduction, failing the class, or, in extreme or repeated cases, dismissal from the program.

FOR MORE INFORMATION

Contact Penny Rheingans, rheingan AT cs.umbc.edu.