Spring 2023 - IAT 814 G100

Visualization and Visual Analytics (3)

Class Number: 4115

Delivery Method: In Person


  • Course Times + Location:

    Mo 2:30 PM – 5:20 PM
    SRYC 5100, Surrey

  • Instructor:

    Lyn Bartram
    1 778 782-7439



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: The class will be in-person only. 


Courses Objectives:

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)

Learning Activities:

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:

  1. Basics of perception and cognition
  2. Visualization and interaction design
  3. Visual analytics - dealing with large volumes of dynamic data and the ideas of linking computational/analysis techniques with interactive informational visualization methods
  4. Data and analytics storytelling
  5. 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.



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.


Your personalized Course Material list, including digital and physical textbooks, are available through the SFU Bookstore website by simply entering your Computing ID at: shop.sfu.ca/course-materials/my-personalized-course-materials.

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.

Registrar Notes:


SFU’s Academic Integrity website 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