The Visual Art Behind Data Science

All Analytics readers like data visualizations -- even though slightly more than 50 percent of the participants in our recent quick poll conceded "the quality is inconsistent."

While none of the 65 respondents explained exactly what they meant by that inconsistency, it's easy to surmise.

And I don't think I can state it any better than Ryan Bell, a user interface developer for EffectiveUI, a digital user experience agency:
As available data becomes more complex and extensive, weaving it into a visualization that invites engagement, understanding, and decision-making is a bigger challenge, with a bigger opportunity for payoff.
Bigger opportunities for payoff -- but, in the wrong hands, those turn into greater opportunities for misinterpretation, especially when we expand the term "data visualizations" to include infographics.

There are so many infographics these days, and so many of them are cluttered, confusing, and, unfortunately, wrong.

Remember that infographic Dylan Matthews at The Washington Post published last month under the headline, "The saddest graph you'll see today"?

The infographic was created by the Enliven Project to put the legal issues around rape, its prosecutions, and concerns about false accusations into perspective. The idea was to visualize the fact that false rape accusations are rare. But critics claim the infographic was misleading in several ways because it assumed one-rape-per-rapist, overestimated the number of unreported rapes, and overestimated the number of false accusations.

Good intentions can get lost pretty easily in a bad data visualization.

Effective data visualizations marry art and science. They transform complete and accurate data with sound visual design elements, like line, form, shape, value, and color. But to do that, and create a visualization that keeps the data in the right context, the graphic artist has to understand the information being visualized.

It's all about the data. As David McCandless, a London-based independent data journalist and information designer, explains, the key to a great data visualization is "good, tight, and comprehensive" data. "The technical term for that is 'juicy.' Juicy data. In fact, 80 percent of the work involved in creating an infographic is data-gathering, shaping, and checking. Making the data juicy," he states.

So, here is the question: How can data professionals and graphic artists work better together to bring data to life -- beautifully, effectively, and without distortion?

Noreen Seebacher,

Noreen Seebacher, the Community Editor of Investor Uprising, has been a business journalist for more than 20 years. A New York City based writer and editor, she has worked for numerous print and online publications. Her work has appeared in The New York Times, the New York Post, New York’s Daily News, The Detroit News, and the Pittsburgh Press. She co-edited five newsletters for Real Estate Media’s and served as the site's technology editor.

She also championed the commercial real estate beat at The Journal News, a Gannett publication in suburban New York City, and co-founded a Website focused on personal finance. Through her own company, Stasa Media, Noreen has produced reports, whitepapers, and internal publications for a number of Fortune 500 clients. When she's not writing, editing, or Web surfing, she relaxes in an 1875 Victorian with her husband and their five kids, four formerly homeless cats, and a dog.

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Re: Share please
  • 2/12/2013 10:26:05 AM

Wow. The rape one is very powerful.

Not so bad ...
  • 2/12/2013 10:25:42 AM

Hi Noreen, I don't really think the Enliven Project data visualization was so horrible myself. It certainly met its mission of raising awareness, even more so because of the brouhaha that followed from it! The lesson I take from it is that at times data visualizations are meant to be taken more conceptually than in hard numbers -- but the designers and editors must make that distinction clear in their presentation.

Re: Share please
  • 2/12/2013 10:14:51 AM

This is nice: 

Share please
  • 2/12/2013 10:04:09 AM

Feel free to share your favorite examples of good or bad data visualizations...

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