GDES-360 spring 2021 / David Ramos, American University Design


Look closely at data about neighborhoods, towns, or small geographic areas. Ask a question about the data, and create a set of visualizations responding to that question. (Work with non-spatial visualizations like line graphs, bar graphs, and proportional area charts.)

Start by finding data sets about that talk about places. You might look at demographics of neighborhoods within DC, a season’s box scores of high school baseball teams in your home county, or graduation rates for womens colleges around the Northeast.

This project is the first of two, related assignments. In this project, Neighborhoods, you’ll be making non-spatial visualizations like line graphs, bar graphs, and proportional area charts. In the next project, Spatial, you’ll look more closely at the location-based facets of your topic, creating a series of maps to accompany your work from Neighborhoods.


A few examples of pieces that mix non-spatial visualization types with maps (mostly thematic/data maps, in these examples).


1. Explore datasets and ask a question

Choose your own datasets. You might return to one of the datasets we used in previous assignments, find something yourself, or try a new one. A few possible data sources follow.

More specialized datasets

Other ways to find ideas

Perhaps, go read the paper; dig up the original studies if need be.

Help with data wrangling

I’m happy to sit with you to help you find datasets that will help you answer your question, so far as I can. (For non-spatial data, I’m best equipped to talk about the ACS and current Census data. I also might point you toward a subject matter librarian.) I may also be able to convert data that are in formats that are not amenable to analysis, either because of organization or file format. Email me and schedule an appointment, or come by office hours.

2. Sit with the data

Start exploring the data, producing rough visualizations to help you understand what’s going on, and arrive at a question to explore. Then examine that question in more depth.

3. Design studies

Start experimenting with ways of visually presenting your data. Think of this as sketching—try different graphic forms, scales, and methods of encoding. At some stage, you’ll also need to consider how to fit this onto the page.

For this project, you need to sketch out several different approaches, with a small but representative amount of real data, but you do not need to develop multiple versions to the final stage.

4. Final design

Polish your rough design. You might want to produce new base graphics from a spreadsheet/stats program. Move on to a more visually expressive and typographically-oriented environment to prepare the final graphics—perhaps Illustrator, another drawing program, or (yes) working by hand.


Include notes about your sources, enough that we know where you got the data from. “Data from 2012–2017 American Community Survey estimates” would be a good answer. For your own purposes, save the exact web addresses so you can go back.

Tools and methods

Use what you like. For manipulating or analyzing data, and for preparing rough visualizations, a spreadsheet or Workbench would serve well. You might want to create your base visualizations using RawGraphs or Flourish—but edit and improve them in Illustrator, another drawing program, or by hand.

For background, return to chapters 4 and 5 from The Truthful Art.

Typography, and font suggestions

This project leans on good typography as much as on the graphic side of information graphics. If you want type tips, look to the “Letter” and “Text” sections of Ellen Lupton’s Thinking with Type site, or check out the book.

Choose legible, well-drawn fonts.

Free/open source suggestions: Source Sans Pro, IBM Plex, Barlow, Cormorant Garamond, Libre Caslon, and Libre Baskerville. (More libre fonts.)

Commercial suggestions: Adobe Minion, Adobe Garamond, Caslon, Frutiger, Trade Gothic, Franklin Gothic, Myriad, Meta, DIN, Helvetica, Jenson, Archer, Gotham, and Whitney.