About the Course

This course is an introduction to working with data for exploration and explanation.

It's a mix of history and theory of information with a series of projects that apply the ideas directly. Students will start with basic data analysis, then learn about visual design and presentation, followed by more sophisticated interaction techniques.

Topics include storytelling and narrative, choosing representations, understanding audiences, and the role of practitioners creating tools to help people work with and make sense of information. Experience with code and/or design preferred, but not expected or required.


One of the best things about this class is the range of backgrounds for the students attending it. Each semester, we've had a mix of both graduate and undergraduate students, from inside MIT and outside (Wellesley, Harvard GSD, Kennedy School, etc), all of them studying a wide range of fields: Architecture, Mechanical Engineering, Media Arts and Sciences, Biology, Computer Science, and others.


This class is not intended to give students a “how to” on creating data visualizations. There are plenty of books, frameworks, and online tutorials for creating interactive toys and prescriptive charts, maps, and graphics. Such tools can be very useful, but it’s something better learned on your own time.

This course will take guidance from a mix of work from inside and outside the field, plus case studies from our studio to demonstrate different ways of looking at narrative and interactive information design.


The “design” of a project is not about what it looks like. It’s about how they work and how they help the intended audience think about a set of data.

The first design attempt will always be insufficient, and many iterations will be required as you refine your ideas. An all-nighter won’t be enough iteration to work through a project. Focus on smaller steps and getting feedback. If this is unfamiliar, it will be one of the most important things you can learn from this course.


This is not a coding class. If you know how to code, you’ll find that part of the course easier, but you’ll still need to put considerable effort into the design and conceptual part of what you create. If you’re not familiar with code, we’ll help you along and can assure you that you’ll be able to figure it out, as long as you participate.

Final Projects

The projects featured were each created by individuals over the course of 4 to 6 weeks, depending on the semester. We start with an initial prompt, where students choose two ideas from the following categories:

  1. Personal
    Some kind of data that you’ve collected over time. The important thing is that it’s something that’s readily available—it won’t work to collect the data for the next couple weeks and then create your final project in the last week.
  2. Research
    While we’re not interested in you doing your final project around work that you’d already be pursuing for your research, this is an opportunity to think about information design questions around your research or thesis.
  3. Explanation
    Take a complex idea that’s data-centric, and making sense of it. Examples include visualizations of algorithms, economic flows, etc.
  4. A data set you’re curious about
    Find a data set that you think is interesting, and telling us a story about it or providing people with a way to explore it. Examples include several of the projects we’ve shown from our own work: the Darwin project, our population density poster, or the Fortune 500 piece.

For the two chosen, explain the data set, and answer address these three sets of questions:

We discuss those ideas as a group, choosing one, which we then develop over the remaining weeks.

MIT 4.032 | Ben Fry | last updated November 2020