CSE512 Data Visualization (Spring 2019)

The world is awash with increasing amounts of data, and we must keep afloat with our relatively constant perceptual and cognitive abilities. Visualization provides one means of combating information overload, as a well-designed visual encoding can supplant cognitive calculations with simpler perceptual inferences and improve comprehension, memory, and decision making. Furthermore, visual representations may help engage more diverse audiences in the process of analytic thinking.

In this course we will study techniques for creating effective visualizations based on principles from graphic design, perceptual psychology, and cognitive science. The course is targeted both towards students interested in using visualization in their own work, as well as students interested in building better visualization tools and systems.

In addition to class discussions, students will complete visualization design and data analysis assignments, as well as a final project. Students will share the results of their final project through both interactive demos and a poster session.

There are no prerequisites for the class and the class is open to graduate students as well as advanced undergraduates (by permission of instructor). Basic working knowledge of, or willingness to learn, graphics/visualization tools (e.g., D3, Vega, HTML5, OpenGL, etc) and data analysis tools (e.g., R, Python, Excel, Matlab) will be useful.

Final Projects will be presented in the Paul G. Allen Center at the University of Washington on Monday June 10, 5-7:30pm.


Learning Goals & Objectives

This course is designed to provide students with the foundations necessary for understanding and extending the current state of the art in data visualization. By the end of the course, students will have gained:

Schedule & Readings

Week 1

Thu 4/4 Data & Image Models Slides

Week 2

Tue 4/9 A1 Review & Re-Design Exercise Slides
Assigned: Assignment 2: Exploratory Analysis (Due: Mon 4/22)
Thu 4/11 Exploratory Data Analysis Slides

Week 3

Week 4

Wed 4/24 D3.js Tutorial, 3:30-5:00pm, Gates Center G20 Notebook

Week 5

Week 6

Tue 5/7 A3 Demos & Critique Slides
Assigned: A3 Peer Evaluation (Due: Mon 5/13)
Assigned: Final Project Proposal (Due: Thu 5/16)

Week 7

Week 8

Week 9

Week 10

Tue 6/4 Final Project Feedback Sessions
Thu 6/6 Final Project Feedback Sessions

Finals Week

Mon 6/10 Final Project Poster & Demo Session (5-7:30pm, Allen Center Atrium)



Late Policy: We will deduct 10% for each day an assignment is late.

Plagiarism Policy: Assignments should consist primarily of original work. Building off of others' work—including 3rd party libraries, public source code examples, and design ideas—is acceptable and in most cases encouraged. However, failure to cite such sources will result in score deductions proportional to the severity of the oversight.

Class Participation

It is important to attend the lectures and read the readings. Each lecture will assume that you have read and are ready to discuss the day's readings.

Class participation includes both in-class participation as well as participation in the discussion on Canvas. All enrolled students are required to submit at least 1 substantive discussion post per week related to the course readings. Each student has 1 pass for skipping comments.

Good comments typically exhibit one or more of the following:


See the resources page for visualization tools, data sets, and related web sites.


Questions should be posted on Canvas. If you have a private question, email the instructors at cse512@cs or come to office hours.