When Al Gore talks about global warming, Hans Rosling shows the relationship between health and wealth, and the New York Times visualizes primary results and American consumer debt, they communicate visually. But they only use visual representation to get their point across, as a means to an end. When we want to show why visualization is effective, we have to care about the message, too – not just the method.
When pitching a tool or a project to a customer, one of the first tricks is showing them their own data. That is how they can relate to what the tool will do for them, rather than having to imagine how the presented toy data relates to what they care about. They see through the tool and see what they know. Or better yet, what they didn’t know about their own data.
The same is true for showing visualization to a more general audience, where there is no “their data.” But there is a lot of data that most people care about when it is presented to them, and that serves the same purpose. And when visualization is used to communicate not just the fact that the data exists, but also interesting and perhaps surprising information about it, people will listen (and watch).
Besides the examples at the very top of this posting, there are lots of others that may be less spectacular, but no less relevant. A recent project by Jeff Heer and colleagues at UC Berkeley together with Minnesota Public Radio looked at unemployment rates by sector in Minnesota over the last eight years. The brilliant Death and Taxes poster/interactive feature shows how the U.S. federal budget is split up between departments and programs, data every tax payer should be aware of (Jess Bachman, its designer, also has a very interesting blog where he looks at visualization problems like how to visualize the magnitude of one billion dollars).
Of course, visualization methods need to be developed by people who care about the visualization method, how it can be applied to different kinds of data, and how it supports different kinds of analysis and presentation.
But a compelling visualization needs a compelling story about interesting data. If it doesn’t have that, it’s no longer about effective visual communication. It becomes visualization porn.
Teaser image from the WallStats blog, used with permission.
For a similar problem in statistics, see “I don’t care about the data …”