How To Craft Truly Awesome Data Visualizations

February 20, 2015 10:22 am PDT | Open Data

Open data advocates and government officials from all over the world come together at the Socrata Customer Summit to dig into data visualization. Jonathan Schwabish, Senior Researcher and Data Visualization Expert with the Urban Institute, breaks it down, challenging open data enthusiasts to, “do a better job, a more effective job, a more strategic job of communicating information.”

For many years, Schwabish explains, “we have followed a fairly typical equation,” which was to, “take a graph and embed it in a report and surround it by a bunch of text.” No one seemed to pay much attention to it, Schwabish noted. He points out data visualization is revolutionizing that pattern; it gets decision makers and the public, “to pay attention to our work, pay attention to our analysis.”

Dynamic communication benefits everybody

The need to communicate relevant, real life stories is at the core of Schwabish’s message. Data visualization done well accomplishes two great things: it helps data producers better understand their own information, revealing meanings and findings, and it organizes complex issues into accessible formats, enabling us, “to grab our audiences,” Schwabish says. “What’s beautiful in our work is the data – that’s what’s important,” and things like data labels and graph legends, he contends, “distract from the effort to effectively communicate.”

The explosion of data visualization technology, from data management tools to open source software to dynamic presentation techniques, makes it easier for stakeholders in small nonprofit organizations as well as large government agencies to, “create visualizations that get our audiences to say, ‘Wow!’” Schwabish says. He notes that presenters seek two types of reactions: either get audiences to lean forward and interact with the display, exploring the data; or, lean back and feel stunned by the display and the technology behind it.

The spectrum of data visualization

Schwabish explains both reactions serve purposes in communicating the data. Once presenters know which reaction they want, they can pursue it by communicating data via spectrums of form and function. Form, he notes, can be static or interactive, with elements like animated graphics occupying the middle zone. With function, data visualizations can go explanatory or exploratory, either telling a compelling story for users to absorb, or giving users opportunities to create their own stories.

To illustrate, Schwabish walks his audience through these categories and their uses. He shows live examples from major media outlets and governmental agencies, dynamic data visualizations that are a big improvement over the days of, “creating third-party 30, 60, 90, 200-page reports that sort of just went out there and disappeared into the ether,” Schwabish reflects.

“It’s important for us as producers of data – as people steeped and rooted in data – to think carefully about the needs of our audience and how our visualization efforts can help them do their jobs better,” Schwabish emphasizes.

Diving into the graphics continuum

Schwabish then attacks the ocean of graphics available to those communicating their data. Noting the vast combinations of, “mapping between data and graphics, and how graphics all relate to one another,” he shows the poster he and his colleagues created to help them sort through their options when crafting data visualizations: almost 90 different graphic types, grouped into six categories. “I call this space the Graphics Continuum,” Schwabish explains.

“We pulled all these types together because it’s interesting to me to think about how all these graphs relate to one another,” Schwabish says. “When people ask me, ‘How do I plot this data?’ I answer, ‘I don’t know – there are lots of different ways. What does your user need, what does your audience want to see?’”

Making it happen: Teamwork powers data visualizations

Actually creating data visualizations, Schwabish acknowledges, takes specific tools and expertise. He runs through a quick list of available software, and then focuses on skillsets, noting three must-have areas: An understanding of statistics, math, or econometrics, “so you can work with the data and be comfortable with it and use it in an appropriate way.” Next, an appreciation of design, since not only are the aesthetics important for captivating users and keeping them there, but also for keeping things honest on the analytical side, with no accidental visual emphasis of one fact over another. Last, you need people, “with understanding of programming, to build these interactive products.”

So, where does Schwabish find these colleagues? He doesn’t. He calls them, “unicorns – because they just don’t exist.” Instead, the goal is, “to build teams and organizations and firms where together we are the unicorn.” He brings it full circle for his audience, noting, “Because if we can do a better job of communicating information, we can improve the world around us. And that I think is the ‘wow’ that we all would like to elicit.” 

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