Data visualization

“Chartjunk?” you ask. “What’s that?” The term comes from Edward Tufte, whose work I have admired for thirty years. If you only have a small amount of time to read what he has written, I recommend the beautiful, 200 page classic, The Visual Display of Quantitative Information, as well as his tiny 32-page treatise, The Cognitive Style of PowerPoint. You’ll learn what to do and what not to do when presenting information graphically. What not to do is to fill your graphics with chartjunk: unnecessary and distracting clutter that makes it hard to discern the message of the graphic. For example, see the image at the bottom of this post.

But if that’s what not to do, what should you do in a graphic? From my previous studies of Tufte and others, I have concluded that a graphic should be accurate, clear, and as simple as possible (“but no simpler,” as Einstein observed). But now I see a fourth criterion: memorability. A recent study at Harvard and MIT has found that memorable graphics are not always the ones that are clear and simple:

“A visualization will be instantly and overwhelmingly more memorable if it incorporates an image of a human-recognizable object—if it includes a photograph, people, cartoons, logos—any component that is not just an abstract data visualization,” says Pfister. “We learned that any time you have a graphic with one of those components, that’s the most dominant thing that affects the memorability.”

Visualizations that were visually dense proved memorable, as did those that used many colors. Other results were more surprising.

“You’d think the types of charts you’d remember best are the ones you learned in school—the bar charts, pie charts, scatter plots, and so on,” Borkin says. “But it was the opposite.”

Unusual types of charts, like tree diagrams, network diagrams, and grid matrices, were actually more memorable.

Definitely food for thought.

chartjunk



Categories: Math, Teaching & Learning