1 Course Description: Prerequisite: Instructor: Office Hours: Textbooks: References: ISE 431/HFE 631: Human Factors of Visual Displays Jan 5 – Mar 21, 2009 Tues & Thur, 2:15 – 3:55pm, Russ 146 The goal of information visualization is the unveiling of the underlying structure of abstract data using visual representations that utilize the powerful processing capabilities of the human visual perceptual system. The objectives of this course are three folds.  Introduce students to concepts and issues related to information visualization  Examine and evaluate various information visualization techniques  Use visualization tools to develop effective information visualization techniques to support information exploration, presentation, communication and decision making HFE 606 or permission of instructor Dr. Yan Liu RUSS 230 Phone: (937)775-5161 Fax: (937)775-7364 Email: [email protected] RUSS 230 Monday & Wednesday, 1:00-3:00 PM or by appointment Ware, C. (2004). Information Visualization Perception for Design, Second Edition. San Francisco, CA: Morgan Kauffmann Publishers. (Required) Card, S.K., Mackinlay, J. & Shneiderman, B. (1999). Readings in Information Visualization: Using Vision to Think. San Francisco, CA: Morgan Kauffmann Publishers. (Recommended) Chen, C. (1999). Information Visualisation and Virtual Environments. New York, NY: Springer. Chen, C. (2004). Information Visualization: Beyond the Horizon. New York, NY: Springer Murrell, P. (2005). R Graphics. Boca Raton, FL: Taylor & Francis CRC Press. Tufte, E.R. (1983). The Visual Display of Quantitative Information. Cheshire, CO: Graphics Press. Tufte, E.R. (1997). Visual Explanations: Images and Quantities, Evidence and Narrative. Cheshire, CO: Graphics Press.2Software: Course Website: Homeworks: Term Project: Grading Criteria: The aim of the term project is for students to better grasp the knowledge gained from the lectures. The project is a group project for ISE 431 students (2 or 3 students per group) but an individual project for HFE 631 students. Note that for ISE 431 students, the project done by a larger group should be correspondingly more sophisticated than that done by a smaller one. Each group/individual is responsible for selecting the specific project topic of interest; it should be related to information visualization of course.  Proposal: A written proposal should be turned in by Jan 15 and Jan 20 for in-class and distance students, respectively. The proposal should describe: i) name(s) of the investigator(s), ii) the problem to be addressed, and iii) a sketch of how you plan to solve the problem  Project Report: The project report is due on Mar 16 and March 20 for in-class and distance students, respectively. The report should include: i) an overall presentation of the problem, ii) the proposed design of the visual display, iii) a discussion of the lessons learned and future work  Project Presentation: Oral project presentations will be scheduled. Sign-ups for the presentations will be available later in the quarter  Grading Criteria: The project will be graded based on the clarity and organization of the writing, originality and effectiveness of the design, and quality of the presentation For graduate students with thesis option, I highly recommend you to think about your own research when deciding the project topic. If your project is of high quality, we can consider submitting it to a conference or even a journal (after some revisions and improvement) http://www.engineering.wright.edu/~yan.liu/HFE631_2009, where you can find information about the course materials, including a questionnaire, syllabus, lecture notes, Homeworks and extra readings. I will try to put lecture notes online at least one day ahead. Your grades will be posted on WebCT (http://wisdom.wright.edu/). Homeworks 40% (20% for each) Project Presentation 20% Project Report 40% The percentage grades needed to achieve an A, B, C, or D will follow approximately the following scale: 90 – 100 = A, 80 – 89 = B, 70 – 79 = C, 55 – 69 = D, 0 – 54 = F. The minimum score needed for a given letter grade could be lowered at the instructor’s discretion, if necessary, but will not be raised. • ILOG Discovery. http://www2.ilog.com/preview/Discovery/ • R. http://cran.r-project.org/ There are two homework assignments which require you to create visualizations for given datasets using ILOG Discovery and R3 My Expectations: Your Expectations:  You can expect that I will work hard in this course  You can expect that I will do my best to explain and illustrate the materials in a way that makes sense to you. Sometimes I will need help and feedback from you in order to figure out the best way to explain something.  You can expect that I will listen to your questions with respect and never ridicule; if the answer to your question is beyond the scope of this course, I will discuss it with you outside of class.  You can expect that I will attempt to evaluate your work fairly and assign grades appropriate to your performance.  You can expect that I will do my best to make this course a success for all of us. If you have other expectations, hopes, or suggestions, please let me know.  I expect that you will work hard in this course.  I expect you to come to each class prepared to listen and understand. I expect that you will ask questions if things are not clear.  I expect that you will use the textbook and other resources and read materials as assigned.  I expect you to attend class regularly and promptly catch up on any classes you miss.  I expect you to make honest attempts at assignments and ask for help when you need it. I expect you to not misrepresent the work of others as your own and neither give nor receive unauthorized aid in assignments. The university standards of academic honesty under academic information can be found in the WSU student handbook, http://www.wright.edu/students/judicial/stu_integrity.html.  I expect you to behave appropriately and politely towards me and your fellow classmates at all