IGR 204: Visualization

IGR 204: Visualization

Instructor
James Eagan
Teaching assistants
Period
Spring 2019 (P4)

Access to data is increasing exponentially, yet our ability to analyze and make sense of them is limited. The goal of information visualization is to provide users with the tools necessary to visually explore, understand, and communicate complex data.

Course goals

  • Introduce the fundamental principles of visualization.
  • Provide an overview of the state of the art and historical work in the domain.
  • Learn how to critically analyze visualizations applied to a particular data analysis task.

This course is taught in English.

Class organization

Classes will generally consist of 1h30 of lecture followed by 1h30 of lab activities. Check the syllabus in Synapses regularly as rooms vary.

Class slides are available from the class Moodle.

Syllabus

Class Topic Homework/Readings
19/04—08h30 Intro, Data & Abstractions Value of InfoVis, Munzner Ch. 1
19/04—10h15 Lab: Turnkey Vis (Tableau) Due: M0 midnight
26/04—08h30 Visual Mappings D3, Munzner Ch. 5
26/04—10h15 Lab: Declarative Vis (Altair) Due: M1, L1 midnight
10/05—08h30 Tasks Task Typology, Munzner Ch. 3 
10/05—10h15 Lab: Intro to D3 Due: Lab 2 midnight
17/05—08h30 Perception  
17/05—10h15 Lab: Design alternatives Due: Labs 3 & 4 midnight
07/06—08h30 Tufte & graphic design Table Lens, Explorable Explanations
07/06—10h15 Lab: Interactivity Due: M2 before class
14/06—08h30 Graphs & Trees Munzner Ch. 9
14/06—10h15 Projects  
21/06—08h30 Scientific Visualisation (SciVis)  
21/06—10h15 Scientific Visualisation (SciVis)  
26/06—08h30 Final Exam (M3)
26/06—10h15 Project presentations (M4)  Due: M5 midnight

* The instructor reserves the right to make and communicate changes to the above schedule.

Discussions

Please use the class Moodle discussion forum. The system is catered to getting you help fast and efficiently from classmates or from the instructors. I encourage you to post questions and discussions there.

Readings

The textbook for this class is Visualization Analysis & Design, by Tamara Munzner. It is available through the link above. In addition to chapters from that book, various scholarly articles will be assigned as in-home readings.

We also recommend Envisioning Information, by Edward Tufte. This book really needs to be read in dead-tree form. You may consult my personal copy in my office. The link here points to Amazon for convenience, but if you wish to purchase it, I recommend using your preferred local book pedlar.

Grading

Grades are determined by three primary criteria:

  • 40% Project
  • 40% Final exam
  • 10% Quizzes
  • 10% Labs & short homework assignments

Grades may be adjusted by up to 5% based on class participation.

Plagiarism policy

All work submitted is expected to be your original work. Feel free to discuss your work with your fellow students, use available resources (e.g., books, articles, web pages, source code), but these resources should serve as inspiration or supporting materials only. Do not forget to cite any such resources appropriately. Failure to appropriately cite your sources may result in a grade of 0 and/or academic sanctions.

Labs & Project