Visualization Trends For The NoosphereJan 30, 2009 In Web Culture By Jon Udell
Data visualization is an expressive medium. We use it to tell stories that help us make sense of the world. For five hundred years we wrote and illustrated those stories for the printed page. Toward the end of the last century, Edward Tufte showed us how much we had yet to learn about envisioning information using ink on paper. And his lessons will always inform our practice. But with data processing tools, networked software, and digital displays, we enter a new era of data visualization -- and not a moment too soon
The world we must make sense of now is one in which human actions have planetary effects. The good news is that we can, for the first time, begin to measure those effects. We’re instrumenting the atmosphere and the oceans, and torrents of data are arriving from our sensors. The bad news is that we’re not yet very skillful storytellers in the medium of data. That’s true both in the specialized realm of science, and more broadly at the intersection of science, public policy, and the media.
The biosphere is, of course, no more complex than it ever was. It just seems that way because we can know more about it. But the noosphere — the swarm of intelligence pulsing through the electronic networks that encircle the planet — is growing more complex every day. Our social, economic, and political lives are ruled by abstractions, and we’ve got to make sense of those too. If we had truly apprehended the global pool of money,and the dynamics of credit default swaps,could we have prevented (or at least blunted) the current crisis? We’ll never know. But if we can produce useful and relevant heads-up displays, maybe we don’t have to fly blindly into the future.
Painting pictures in the medium of data requires a daunting array of talents. For starters, somebody has to mix the paint. Although data is plentiful, it’s rarely available in a useful form. One of the visualizations presented here uses data from the Centers for Disease Control. You’d think it would be straightforward, in 2009, to acquire data on the incidence of obesity, state by state, for the past 20 years. Not so. The MIX Online team had to download hundreds of megabytes of data from the Centers for Disease Control, in SAS transport format, and then write an R script to parse it. Mixing the paint shouldn’t be so hard. Publishers need to work harder to deliver data in more useful packages. Meanwhile, data harvesters will continue to labor behind the scenes.
One of the first benefits of visualization, by the way, is to check the quality and consistency of data. Do the numbers even add up? Often they don’t. Most data repositories are seen by very few eyes, and touched by very few hands. When we make source data visible and tangible, more eyes and hands can help ensure that the numbers measure what we think they measure.
Given reasonably clean data, how do we interpret the numbers? And how do we empower others to make their own interpretations? Graphic artists, statisticians, interaction designers, programmers, and cinematographers all possess relevant skills. Only a handful of organizations can employ multidisciplinary teams that draw on all these domains of expertise.
To democratize visualization we’ll need a new generation of software. With personal and then web-based computing, we’ve seen it happen again and again: spreadsheets, desktop publishing, web multimedia, cloud-based services. Now, across a range of devices as well as in the cloud, we have the raw technologies to democratize the visualization — and collaborative analysis — of data.
The challenge is to combine all these ingredients into toolkits that don’t require developers, or even an ordinary users, to be expert in a dozen disciplines. What will those toolkits need to be? Honestly, we’re not sure. Watching as the industry solves these problems is half the fun. In the meantime, this issue of MIX Online explores the user experience side of this question.