[infosthetics@strataconf 2011 by guest blogger Collin Sullivan]
The above graphic is 150 years old, and it popped up more than a few times on Wednesday, which was Day 2 of the 2011 Strata Conference. Charles Joseph Minard designed it in 1861, and it depicts Napoleon's ill-fated march to and from Russia nearly 50 years before. The line is light as Napoleon and his army march toward Moscow, and solid black as they retreat. The line's thickness depicts the size of Napoleon's army at the corresponding place on the map, and we can follow along as it thins dramatically over time. [see it also here]
Minard's graphic is a classic in the field, as it should be. It is considered both beautiful and parsimonious; from just a small amount of space we can glean a lot of information. Perhaps the single characteristic that makes this map most effective, though, is that it tells a story.
Pete Warden of OpenHeatMap believes that humans are natural storytellers. In the Visualizing Shared, Distributed Data panel discussion on Wednesday, he told us, "Our brains are hard-wired for stories." Stories are how we communicate with one another, how we share information. Narratives provide the context within which we make sense of data. And in talk after talk, data visualization was presented as a medium by which we can tell a story.
It makes sense. The information packed so neatly into Minard's map would fill dozens of spreadsheet rows, and writing the information out in narrative text form would be laborious and, in the end, likely ineffective. Data simply lends itself to visualization.
But as is true with all types of storytelling, some approaches are more effective than others. That was the topic of two of the morning discussions Wednesday, one given by Tableau Software's Jock Mackinlay and the other from Kim Rees of Periscopic. Rees spoke on visual economy (Small is the New Big: Lessons in Visual Economy, slides available here), focusing on the succinct and the necessary. Graphs and charts can and ought to be beautiful, but it can and should be done without extraneous information and without wasting space. She showed a beautiful infographic displaying attempted missions to Mars as an example:
The graphics are close but not cluttered, and the information is plentiful but not overwhelming. The chart is concise and complete; in a word, succinct. Rees emphasized that word, among others that suggested things should be small, compact, dense-but-readable. Most importantly, though, the narrative is clear. We can see successes and failures, visually distinguish between countries, follow along on a timeline. Another great example she used:
This tells a pilot all she needs to know about the relationship between the plane and the horizon. Including additional numbers or degree measurements would add only clutter here, as this quickly answers the only question the pilot is asking at the moment: Is the plane level? There is no need for trees or further landscape design, no labels for the sky or the ground. The color selection does that work for us. The context is minimal but the information is adequate.
If Rees' talk was about how to visually frame the narrative, Mackinlay's presentation was about how to tell the story itself (Telling Great Data Stories Online). He implored us to allow the data to decide the visual medium. That is, we should not find a graph we like and force the data to fit into it. Instead we should identify which graph fits best for this or that particular data set. The visualization, he said, ought to communicate all of the relevant information, but in a way that leverages what Mackinlay called the "human perceptual system" (remember the Gestalt Laws from Tuesday afternoon's talk with Naomi Robbins). Here is an example he used:
The graph on the right works better because it uses color, rather than size, to identify the variables. Our brains automatically assume that if a data point has a greater area, it is somehow larger than or superior to the other data, and it draws our eye. But in the graph on the left, size is used only to suggest differing regions, the area of which is not important here. It communicates something that it should not. (Robbins bemoaned bubble charts partially for this reason, and also for the difficulty of comparing relative sizes in a small space when the differences are subtle).
The best things a person can do to become a better storyteller, Mackinlay told us, is first to look at good examples of visual storytelling, and then to have a proofreader or editor. The presentations at this conference have provided a wealth of the former, and there are plenty of places on the web to find more (Tableau, Google Fusion Tables, The Guardian's DataBlog, Periscopic, etc.). And as storytelling emerged as one theme of Day 2, the question of proofreader or editor segues nicely into another prominent theme, that of dialogue between user and graph. My next dispatch from Strata will explore some of the ways this idea manifested on Wednesday.
This post was written by Collin Sullivan. He is a research analyst for The Sentinel Project for Genocide Prevention, where data collection, analysis and visualization are being used to design an Early Warning System (EWS) to detect and prevent genocide. Collin lives in San Francisco. You can reach him at collin [at] thesentinelproject [dot] org and follow him on Twitter at @inciteinsight.