Spring 2018 - IAT 355 D100

Introduction to Visual Analytics (3)

Class Number: 4727

Delivery Method: In Person

Overview

  • Course Times + Location:

    We 9:30 AM – 12:20 PM
    SUR 3240, Surrey

  • Exam Times + Location:

    Apr 12, 2018
    3:30 PM – 6:30 PM
    Location: TBA

  • Instructor:

    Lyn Bartram
    lyn@sfu.ca
    1 778 782-7439
  • Prerequisites:

    IAT 201 and IAT 267 and either IAT 265 or CMPT 225 or other approved second year programming course. 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.Basic Graphics for Visualization: students learn how to represent simple objects in two dimensions and how to manipulate the properties of these objects using standard computer graphics methods and libraries. They learn the basics of two-dimensional representations through graphical two-dimensional transformations, using Javascript and the visualization toolkit D3.

- data structures

- vector / raster graphics

 

- basic rendering

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. Perceptual and cognitive issues are covered.

- introduction to information visualization

- Design principles from visual perception and attention

- Timelines

- overview + detail/focus + context

- using color in information display

- space and order

- depth/occlusion

- trees and graphs

- brushing and linking

- filtering

- interaction and navigation

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. Topics include:

- perceptual issues

- structuring data

- data mining methods

- sensemaking processes

- applications

Grading

  • Assignments 35%
  • Project 25%
  • Final Exam 40%

Materials

REQUIRED READING:

"Interactive Data Visualization for the Web:  An Introduction to Designing with D3" (2017) by Scott Murray; 2nd Edition; O'Reilly Media
ISBN: 9781491921289

"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

“Visual Thinking:  for Design” (2008) by Colin Ware; 1st Edition; Morgan Kaufmann; available as an eBook in the library.
ISBN: 9780123708960

Registrar Notes:

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