Spring 2022 - IAT 814 G100
Visualization and Visual Analytics (3)
Class Number: 2304
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.
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. The goal of this class is to provide students with a basic grounding in techniques that can be used to design and use complex information workspaces, as well as an introduction to theories that help inform the design of such systems. Students will use modern visualization and programming environments to design, apply and critique visual analytics solutions to real-world cases.
NOTE: This course will be offered as a mixed-mode. Students and instructor would meet synchronously online for 90 minutes each week. The remaining course interactions would be asynchronous. If the course is offered as a mixed-mode the timings of the synchronous schedule would be set according to student needs at the beginning of the course. When final determination of the delivery mode and timings are made the outline will be updated.
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:
- Basics of perception and cognition
- Visualization and interaction design
- Visual analytics - dealing with large volumes of dynamic data and the ideas of linking computational/analysis techniques with interactive informational visualization methods
- Data and analytics storytelling
- Data and statistical tools and environments for visual analysis
- Assignments 50%
- Project 50%
The course project is the backbone of this course: students will work together on real-world problems to develop a visual analytics approach to the data.
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.
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS
SFU’s Academic Integrity web site http://www.sfu.ca/students/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
TEACHING AT SFU IN SPRING 2022
Teaching at SFU in spring 2022 will involve primarily in-person instruction, with safety plans in place. Some courses will still be offered through remote methods, and if so, this will be clearly identified in the schedule of classes. You will also know at enrollment whether remote course components will be “live” (synchronous) or at your own pace (asynchronous).
Enrolling in a course acknowledges that you are able to attend in whatever format is required. You should not enroll in a course that is in-person if you are not able to return to campus, and should be aware that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes.
Students with hidden or visible disabilities who may need class or exam accommodations, including in the context of remote learning, are advised to register with the SFU Centre for Accessible Learning (firstname.lastname@example.org or 778-782-3112) as early as possible in order to prepare for the spring 2022 term.