CSE442 Data Visualization (Fall 2018)

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 and algorithms for creating effective visualizations based on principles from graphic design, perceptual psychology, and cognitive science. Students will learn how to design and build interactive visualizations for the web, using the D3.js (Data-Driven Documents) framework.

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 as both an interactive website and a short presentation.


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

Fri 9/28 Data & Image Models Slides

Week 2

Wed 10/3 A1 Review Slides
Assigned: Assignment 2: Exploratory Data Analysis (Due: Tue 10/16)

Week 3

Tue 10/9 Tableau Tutorial - 4:00-4:45pm, 153 Mueller Hall
Wed 10/10 Visual Encoding & Design Slides
Fri 10/12 Interaction Techniques Slides

Week 4

Wed 10/17 Visualization Tools Slides
Assigned: Assignment 3: Interactive Visualization (Due: Tue 10/30)

Week 5

Wed 10/24 D3.js Tutorial Slides

Week 6

Wed 10/31 Prototype Demos Slides
Assigned: Peer Evaluation (Due: Tue 11/6)
Assigned: Final Project (Multiple Due Dates)

Week 7

Fri 11/09 Maps Slides

Week 8

Week 9

Wed 11/28 Design Feedback Sessions
Fri 11/30 Design Feedback Sessions

Week 10

Fri 12/7 Final Project Showcase



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. Up through week 8, 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. Links to the Canvas discussion for weeks 1-8 are included in the schedule above.

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 cse442@cs or come to office hours.