How Research-Driven Organizations Become Thought Leaders

Data Viz Solution: Small Multiples

I love how Pew Research Center displays information — especially in ways that allow you to make quick comparisons and immediately grasp differences.

But I didn’t know how to describe how Pew does this so well until I read this article by the Center’s design director, Peter Bell.

In a phrase: small multiples.

“Small multiples” is a term popularized by Edward Tufte. It means breaking up data that one would conventionally display in a big time series chart into small, multiple charts. Using small multiples makes your charts more legible, lets you convey large amounts of information in small spaces, and allows your audiences to make quick comparisons and get the narrative of a chart without resorting to a legend. Here’s what Bell says about the above chart:

At the Center, our reports rarely show more than five lines on a single time series chart because such a chart is usually hard to read. It can be difficult to distinguish and directly label more than a few overlapping lines in a single plot, and it often requires a color legend with several items. Imagine the seven lines in the graphic above on a single panel. Every line except for Japan’s would overlap with the others.

Imagine, for instance, trying to take in all the below information on a single chart:

I rarely see research-driven organizations use small multiples. But once you see how Pew does it, you see how you should be doing it all the time.

How to do small multiples (how to use Excel or R to execute them) as well as guidelines that Pew follows for titles and labels, style and scale, reference lines, panel order, and annotation and explanation — all these issues are treated in Bell’s fantastic piece, which should be part of your visual reference library. And if you communicate research and expertise, you should regularly read the center’s Decoded channel on Medium.