Fall 2021 - IAT 355 D100

Introduction to Visual Analytics (3)

Class Number: 4899

Delivery Method: In Person

Overview

  • Course Times + Location:

    Mo 10:30 AM – 12:20 PM
    SRYC 3240, Surrey

  • Prerequisites:

    IAT 201 and IAT 267 and either IAT 265 or CMPT 225, all with a minimum grade of C-. Recommended: IAT 235.

Description

CALENDAR DESCRIPTION:

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.

COURSE DETAILS:

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:

Courses Objectives:

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)

Learning Activities:
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. 

  1. 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
  2. Information Visualization: students are introduced to methods of representing and interacting with complex collections of abstract information, including techniques based on color, space, and order, trees, graphs, and networks, detail and context, filtering, brushing, and navigation. They learn the basics of two-dimensional representations through graphical two-dimensional transformations, using Javascript and the visualization toolkits D3 and/or Vega.
  3. 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.

Grading

  • Assignments (Individual) 50%
  • Project (2-person team) 20%
  • Quizzes (Individual) 30%

Materials

REQUIRED READING:

"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.
ISBN: 9781466508910

RECOMMENDED READING:

"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.
ISBN: 9781592538065

"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

Registrar Notes:

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 FALL 2021

Teaching at SFU in fall 2021 will involve primarily in-person instruction, with approximately 70 to 80 per cent of classes in person/on campus, with safety plans in place.  Whether your course will be in-person or through remote methods 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 (caladmin@sfu.ca or 778-782-3112) as early as possible in order to prepare for the fall 2021 term.