Data Visualization Workshop (2017)

July 13-14, 2017
(Instructor: Alexander Lex and Miriah Meyer)

The amount and complexity of information produced in science, engineering, business, and

everyday human activity is increasing at staggering rates. The goal of this course is to expose

you to visual representation methods and techniques that increase the understanding of

complex data. Good visualizations not only present a visual interpretation of data, but do so by

improving comprehension, communication, and decision making.

In this course you will learn about the fundamentals of perception, the theory of visualization,

good design practices for visualization, and how to develop your own web-based visualizations

using HTML5, CSS, JavaScript, SVG, and D3.

 

Note: To participate in this course students must have a laptop with Anaconda installed. Students may also benefit from having WebStorm, but this is not required.

Course Content

  • Intro

              ○ Why visualization?

              ○ Definition of visualization

              ○ Components of a visualization tool

                        ■ Visualization

                        ■ Interaction

                        ■ Multiple views

  • Data abstraction

             ○ Types of data

                       ■ Tables, graphs, fields, …

             ○ Attribute types

                      ■ Categorical, ordinal, quant, …

             ○ Data abstraction exercise

  • Encoding channels

             ○ What they are, how do we use them

  • Perception & Cognition

○ Where do rankings come from

■ Weber’s law

■ Stephen’s power law

■ Gestalt principles

■ The power of the plane

○ Perception, and in particular, why color is hard

■ Short primer on color

  • Design Guidelines

○ Tufte’s 3 integrity principles

○ Pie chart debate: ie. the subjectiveness of good vis

○ Chart junk: good or bad?

○ No unjustified 3D

○ Get it right in black and white

○ Animation

  • Visualization techniques for different data types

           ○ Tables

           ○ Graphs

           ○ Maps

  • Design patterns for multiple views

          ○ Small Multiples

          ○ Overview + Detail

          ○ Multiform

          ○ Dashboards

  • Visualization Process

         ○ User-centered process

         ○ Evaluation throughout

  • Visualization Design Studio
  • Building Interactive Visualizations

         ○ Overview of available Tools and Libraries

         ○ Technical Skills: Interactive Visualization on the Web with D3