Spring 2023 - IAT 355 D100
Introduction to Visual Analytics (3)
Class Number: 4093
Delivery Method: In Person
Course Times + Location:
Jan 4 – Apr 11, 2023: Tue, Thu, 4:30–5:50 p.m.
1 778 782-7439
Prerequisites:IAT 201 and IAT 267 and either IAT 265 or CMPT 225, all with a minimum grade of C-. Recommended: IAT 235.
Focuses on the design and implementation of interactive computer visualization techniques for the analysis, comprehension, and explanation of large collections of abstract information. The application of principles from perception, information visualization, interaction and visual analytics will be covered. Introduces tools for programming geometric information and displaying the results. Emphasizes development of practical skills in using graphics libraries and tools: students will develop programming experience with relevant examples and techniques.
This course focuses on the design and implementation of interactive computer visualization techniques for the analysis, comprehension, and explanation of large collections of digital data. The application of principles from perception, information visualization, interaction, and visual analytics will be covered. Introduces tools for programming geometric information and displaying the results. Emphasizes development of practical skills in using graphics libraries and tools; students will develop programming experience with relevant examples and techniques.
COURSE-LEVEL EDUCATIONAL GOALS:
By the end of this course, students will be able to:
Design and implement 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)
This course is divided into three parts: introduction to basic graphics for information visualization, techniques, algorithms and methods for interactive information analysis and visual analytics.
- Foundations of Visualization: students learn how the representation of simple visual forms supports or impedes perception and interpretation of their meaning. Perceptual and cognitive issues are covered. Basic design principles for visual encoding are introduced and motivated with practical examples, based on design principles from perception and visual attention
- Visual Analytics: students are introduced to dealing with large volumes of dynamic data and the ideas of linking computational/analysis techniques with interactive informational visualization methods
Students will learn both theoretical methods and practical programming implementations using modern web-based languages and tools.
- Assignments 50%
- Final Project 20%
- Visualization journal 10%
- In-class activities and quizzes 20%
"Visualization Analysis & Design" (2014) by Tamara Munzner; 1st Edition; A K Peters/CRC Press; available as an eBook (http://proquest.safaribooksonline.com.proxy.lib.sfu.ca/9781466508910) in the library.
"Design for Information: An Introduction to the Histories, Theories & Best Practices behind Effective Information Visualizations" (2013) by Isabel Meirelles; Rockport Publishers; available as an eBook in the library.
"Interactive Data Visualization for the Web: An Introduction to Designing with D3" (2017) by Scott Murray; 2nd Edition; O'Reilly Media ISBN: 9781491921289
“Visual Thinking: for Design” (2008) by Colin Ware; 1st Edition; Morgan Kaufmann; available as an eBook in the library. ISBN: 9780123708960
REQUIRED READING NOTES:
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.
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS
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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