Course Announcement

Course Announcement for Spring 2015:

Visualization: getting from data to understanding

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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 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 class is more about what pictures to make to understand data than how to make them. We will spend a lot of time understanding design principles. We will not spend lots of time talking about how to program them.

This course was taught in 2012 (see the course web). This offering will be an evolution: last time we had the right concepts, but this time we’ll try better ways to teach it. The class was also taught in 2010 (see the course web) as an initial experiment. The class is modeled after successful classes at Georgia Tech (7450) (Harvard (cs171) and Berkeley (cs294).

This class is offered as a special topics class for the Spring of 2015. In the future, it will become a regular class with its own numbers.

Some Basic Data:

Instructor: Mike Gleicher

Time: Tuesday/Thursday 11-12:15.

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

Prerequisites: None. If you have programming experience, you will have the opportunity to make use of it. If you don’t know how to program, there will be other ways to do the assignments. 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.

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 as part of their projects. Students without significant programming experience should sign up for 638.

Readings: mostly from an online reader. There may be a textbook (last time the textbook was available online from the library – this time we might choose a textbook that is about to be published). Check the 2012 class readings for an idea of what it might be like, although the list will be updated a bit.



Visualizations range from crayon sketches on the back of a napkin to immersive virtual reality displays 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 syllabus from 2012.

What is this class?

If you are interested in working with data, especially in understanding the “human side” of it, then this class is for you.

This class is more about what pictures to make to understand data than how to make it. We will spend a lot of time understanding design principles. We will not spend lots of time talking about how to program them.

If you can’t program, don’t worry. We’ll find other ways for you to make pictures. We will not teach you to program.

If you can program (and like to do it), don’t worry. We’ll let you do some programming to make pictures.

If you only care about getting help with your pet data set from your research, this class may or may not help you. You’ll learn lots of general visualization concepts that will help you with your specific problems in the future, and you might have opportunities to try things on your own data sets for the assignments and projects. Plus, you’ll meet a whole bunch of people who will know a lot about visualization by the end of the semester – so you can get them to help you.

Some logistical details

  • This class will count as a CS elective for the CS undergraduate majors.
  • This class is listed as “full” (or wait list only) until CS students have a chance to enroll. There should be enough space for everybody. But, if you’re interested, please sign up on the wait list. No one can enroll until November 10th.
  • I am not sure if the class will count for core credit for the CS Masters degree, or for the PhD breadth requirement. If this is important to you, consult GAC.



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