Spring 2018 - IAT 355 D100
Introduction to Visual Analytics (3)
Class Number: 4727
Delivery Method: In Person
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
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.
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.
- 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
- overview + detail/focus + context
- using color in information display
- space and order
- trees and graphs
- brushing and linking
- 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
- Assignments 35%
- Project 25%
- Final Exam 40%
"Interactive Data Visualization for the Web: An Introduction to Designing with D3" (2017) by Scott Murray; 2nd Edition; O'Reilly Media
"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.
“Visual Thinking: for Design” (2008) by Colin Ware; 1st Edition; Morgan Kaufmann; available as an eBook in the library.
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