This is the course website for HCDE/DATA 511: Information Visualization/Data Visualization and Exploratory Analytics.

Recent advances in computation, data management, and sensors are leading our society to generate an ever-increasing flood of digital information. Submerged within the data deluge lies a wealth of information that is potentially valuable to businesses, governments, scientists, and all human communities. In order for data to be of use to humans, we need to understand how to explore and communicate this information effectively so that humans can make sense of and draw valuable insights from the data around us. The visual system is the highest bandwidth channel into the human brain.

The goal of data visualization is the unveiling of the underlying structure of large or abstract data sets using visual representations that utilize the powerful processing capabilities of the human visual perceptual system.


Cecilia Aragon
407A Sieg Hall
Office Hours: Thursdays 4-5pm in 407A Sieg
Email: aragon (at) uw. edu


Taylor Scott
424 Sieg Hall
Office Hours: By appointment
Email: omni (at) uw. edu

Course Summary

This course covers the key design principles and techniques used in visualizing, exploring, and analyzing very large data sets, together with the perceptual principles that support them. It is structured to provide both concrete experience with real data and tools as well as a broad overview of the rich world of data visualization. Students will learn both how to design and how to explore, analyze, implement, and evaluate.

The following topics will be included: The design and presentation of digital information. Use of graphics, animation, visualization software, and hypermedia in presenting and analyzing large and complex data. Vision and perception. Methods of presenting vast and complex data sets to enhance comprehension and analysis. Incorporation of visualization techniques into human-computer interfaces.

There are many related topics that this class will not address. These include: computer graphics and visualization as an artistic enterprise.

Students will be required to do reading assignments, perform in-class exercises in design and analysis, participate in online and in-class discussions, and complete several visualization assignments and a group project that will consist either of creating or enhancing a visualization system or technique. Projects will be interdisciplinary in nature and in most cases will involve programming, visualization design, and user interface design. Students will be expected to write up the results of the project in the form of a research paper. There will be no final exam.

This course is based on many prior courses in visualization, including material from UC Berkeley professors Marti Hearst and Maneesh Agrawala, UW CSE professor Jeffrey Heer, UW HCDE instructor Polle Zellweger, and many others. We would like to gratefully acknowledge the generosity of these professors and other experts in sharing teaching materials. All material is used with permission.

Student Learning Goals

By the end of this course, students will be able to:

Class Meetings

Class meets Thurs 6:00pm-9:50pm in 233 Sieg Hall, the Design Lab on the second floor. The format of the class will be a mix of lecture, discussion, analyzing visualizations, in-class activities, and design studio.


Grades will be determined as follows:

Late assignments will not be accepted after the first week of class. In-class work and class participation cannot be made up. If you miss a class, you will receive a zero for the work done in class that day. Please do not ask the professor or TA what you missed during class; check the website or ask a classmate. Required posts to the class discussion board must be made before the due date or you will receive a zero for that work.

Final projects cannot be turned in late.

Readings and Books

Readings will consist of one required text: Stephen Few's Now You See It, and a number of papers that will be accessible online or handed out in class.

Highly recommended but not required:

Guide to using the Tableau software package:
The Beginner's Guide to Data Visualization.


We'll be using the Tableau software package. It works under Windows and Mac. You will receive a code for accessing it; do not share this with others. All students receive free access to Tableau's data visualization software through the Tableau for Teaching program.

You may also use the free Tableau Public software package.

Optionally, you may also be working with R or d3, a free JavaScript library for manipulating documents based on data, or other visualization tools or programming languages. See the resources page for further tools.


The following general policies apply to this course: