Fall 2017 - IAT 814 G200
Knowledge, Visualization and Communication (3)
Class Number: 8220
Delivery Method: In Person
Provides a cognitive and computational framework for understanding and designing graphical and visual representations. Investigates several psychological and computational models of diagram processing, and explores diverse interactive graphical systems.
**NOTE** All seats in IAT 814 G200 are reserved for students in the Big Data program. SIAT students cannot register in this section.
This course will provide an introduction to the fields of information visualization and visual analytics: the science of analytical reasoning supported by highly interactive visual interfaces. We will study techniques and algorithms for creating effective visualizations based on principles from graphic design, visual art, perceptual psychology, and cognitive science. Topics include perception, visualization design, and analytical techniques of working with data. The analytical work that people do includes such information seeking tasks as browsing, search, comparison, selection, and the formulation of hypotheses on the basis of observing collections of data.
COURSE-LEVEL EDUCATIONAL GOALS:
The goal of this class is to provide students with a basic grounding in techniques that can be used to design and complex information workspaces, as well as an introduction to theories that help inform the design of such systems. By the end of this course, students will be able to:
Design and analyze interactive visualization and visual analytics techniques to support human activities
Describe visualization design guidelines, explain the guidelines in terms of human perception and cognition
Describe major sub-disciplines within the fields of visualization and visual analytics
Delivery Method: Lecture (LEC) and Open Lab (OPL)
The course is roughly structured into lecture, seminar and design components. Students will participate in seminar discussions as well as engage in both research-oriented and practical reviews of visual analytics approaches. The following major topics will be covered:
- Perception and Cognitive Principles
- Visual Thinking Visualization in practice: scientific, information and affective
- Visually Encoding Data Visual Idioms and Visualization Forms
- Exploratory Data Analysis
- Multidimensional Visualization
- Interaction and Navigation
- Temporal and Spatial data
- Data Storytelling
- Assignments 50%
- Project 50%
MATERIALS + SUPPLIES:
Course resources, required readings and materials are continually updated on Canvas and on the course website.
“Visual Thinking for Design” (2008) by Colin Ware; Morgan Kaufman - available as eBook in the library
"Visualization Analysis and Design", Tamara Munzner. Available as an ebook (http://proquest.safaribooksonline.com.proxy.lib.sfu.ca/9781466508910) in the library
“Information Visualization: Design for Interaction” (2007) by Robert Spence; 2nd Edition; Prentice Hall
"Design for Information", Isobel Merreilles, 2013. Available as an eBook in the library.
Graduate Studies Notes:
Important dates and deadlines for graduate students are found here: http://www.sfu.ca/dean-gradstudies/current/important_dates/guidelines.html. The deadline to drop a course with a 100% refund is the end of week 2. The deadline to drop with no notation on your transcript is the end of week 3.
SFU’s Academic Integrity web site http://students.sfu.ca/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating. Check out the site for more information and videos that help explain the issues in plain English.
Each student is responsible for his or her conduct as it affects the University community. Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS