Course Announcement

Course Announcement for Spring 2012:

If you’re looking for the 2015 announcement, it is here.

CS838/CS638:
Visualization: getting from data to understanding

This course will explore the foundations of visualization: how we turn data into pictures to help in understanding or communicating it. We’ll cover visualization in the broad sense: including scientific visualization, information visualization (the presentation of abstract data), and visual analytics (the use of interactive tools for exploring large and/or complex data sets).

Visualization is a mix of perceptual psychology, cognitive science, design, computer graphics, data analysis, statistics, human computer interaction, system building, etc.

The course is aimed to serve two different types of students:

• students who work with data and want to understand how to better create and use visualizations in their work (e.g. students in the sciences or humanities)
• students who are interested in creating tools to help people work with data (e.g. computer scientists and statisticians)

In order to serve the range of students who may be interested, the class is offered with two separate numbers: as an undergraduate topics class (CS638) and as a graduate topics class (CS838). The classes will meet together, but have different expectations.

This course was taught in 2010 (see the course web) as an initial experiment. While the 2012 offering will still be an experiment, it should be much more thought out. The class is modeled after successful classes at Harvard (cs171) and Berkeley (cs294).

Some Basic Data:

Instructor: Mike Gleicher

Time: Monday/Wednesday/Friday 11-12:15. Note: this class is “overscheduled” – on average, the class will meet for 150 minutes per week (since its a 3 credit class). The extra time will give us flexibility in adapting the class to meet the needs of the range of students. Generally, we’ll meet twice a week for lectures (Monday and Wednesday), and use Fridays for optional activities like group meetings and lab sessions.

Intended Audience: Graduate or advanced undergraduates either in CS, or in some domain where data is used.

Prerequisites: None. Some programming ability is useful. Some basic statistics is useful too.

Course format: class lectures, discussions (in class and online), readings, design exercises. 838 (grad class) students will be required to do projects involving presentation.

Course Levels: Students should be able to enroll as either CS838 or CS638 (grad or undergrad level). The level of expectations will be adjusted based on levels. 638 students will be given alternatives to projects, while 838 students will be given alternatives to regular assignments. 838 students will be expected to do some implementation. Students without significant programming experience should sign up for 638.

In the past, these mixed level classes really haven’t been too different.

Readings: mostly from an online reader. There may be a textbook (probably similar to 2010).

Overview

Visualizations range from crayon sketches on the back of a napkin to immersive virtual reality display of the fluid dynamics around an airplane; from a bar chart in excel to a fancy, realistic 3D model.

Our goals are to understand the principles that lead to effective visualizations across this range (design, the use of color and motion, basic design patterns, dealing with high-dimensional data, …), specific visualization designs and problems (treemaps, scatterplot matrices, focus+context, volume visualization, …), as well as looking at the kinds of systems and tools that support the creation of good visualizations.

By the end of the course, we will learn how to design effective visualizations for the kinds of data we want to interpret and understand the kinds of tools that support the creation of such visualizations.

You can get an idea of the kind of topics by looking at the 2010 offering of this course.