Data Visualization

This is the course website for CS444, Data Visualization.

Welcome to CS444, Data Visualization. In this course, you will learn how, and why, to create data visualizations. Please read the syllabus carefully, and contact the instructor should you have any questions about its content.

A “visualization” is simply a visual representation of an object of our interest. It’s visual: we consume them with our eyes, and so it is essential that we know how our eyes work — and, more importantly, the parts of our brains connected to our eyes. It’s also a representation; we get to choose what this representation will be, and different choices lead to different pictures, some good and some bad. We will learn how to tell those apart, and how to make pictures that are more good than bad.

Good data visualization involves perceptual psychology, mathematics, and computer science. This makes our subject uniquely challenging: sometimes the way our eyes work stands in way of applying some beautiful result from computer science. Sometimes it’s the other way around: something deep about the math in the data will help guide the design process and let us make a picture that is beautiful, informative, and truthful.

The content of the course is split roughly in three distinct aspects: mechanics, principles, and techniques.

Course syllabus

The syllabus for the course is available here.

Class materials

Assignments

Lectures

  Date Topic Materials
Intro 01/11 Introduction slides
Mechanics 01/16 HTML/CSS/SVG Basics no slides
  01/18 Javascript Basics A2 no slides
  01/23 Javascript + DOM, SVG no slides
  01/25 d3 intro A3 no slides
  01/30 d3 joins and scales no slides
Principles 02/01 Color vision A4 slides
  02/06 Color vision slides
  02/08 Other perceptual channels A5 slides
  02/15 Other perceptual channels A6 slides
  02/22 Interaction slides
  02/27 Design Criticism, Algebraic Design slides
Techniques   Basic Spatial Arrangements slides
    cont’d.  
    High-Dimensional Data slides
    High-Dimensional Data  
Review   Review slides
    MIDTERM  
    Catchup  
    Hierarchies slides
    Graphs slides
    Graphs+Spatial Data slides
    Spatial Data slides, slides 2
    Spatial Data slides 2
Topics   Cartography slides
    Large Data slides
    Thanksgiving, no class  
    Putting it all together  
    The Human Side of Data  
    Retrospective, Review slides

Resources

Schedule

Mechanics

Principles

Techniques

Planned material

Mechanics

Principles