Some examples we will discuss

Information visualization helps people explore or explain data through interactive software that exploits the capabilities of the human perceptual system. A key challenge in information visualization is designing a useful spatial mapping of a dataset that is not inherently spatial and coupling that mapping to interaction techniques that allow people to intuitively explore the dataset. Information visualization draws on the intellectual history of several traditions, including computer graphics, human-computer interaction, cognitive psychology, semiotics, graphic design, statistical graphics, cartography, and art. The synthesis of relevant ideas from these fields with new methodologies and techniques made possible by interactive computation are critical for helping people keep pace with the torrents of data confronting them.

Students will learn how to design and build interactive visualizations for the web, using the Vega-Lite and D3.js (Data-Driven Documents) frameworks.

Learning Objectives:

In this course, you will develop the following skills and knowledge:

  1. To analyze the characteristics of a data set, its primary items, its attributes, and the potential insights that can be gained from the data set.
  2. To explore the design space of visualizations for a data set and discuss the benefits and drawbacks of alternative designs.
  3. To design and develop web-based representations of a visualization that allows users to explore that data set and derive insights from it.

How do we assess these outcomes?

Outcomes will be assessed through the following deliverables:

  1. Students will participate in in-class exercises in which they will assess a real-world data set, design visualizations to support its analysis on paper, and discuss the merits of their proposed visualization in a group setting. The quality of their work in these sessions (and overall willingness to take part) is used to determine their overall participation grade in the course.
  2. Students will take a midterm and a final exam to assess their understanding of both the assigned reading and in-class materials. Students will demonstrate familiarity with historical representations of data, cutting-edge research in visualization, and good design principles for simple data sets
  3. Students will undertake several take-home assignments that assess their ability to design visualizations and their ability to develop visualizations using real data. These assignments are structured in parallel with a course project to help them develop the programming skills necessary to develop a novel visualization system.
  4. Students will submit and present a final project that takes a real data set and represents its important characteristics in an interactive way.