Rev Up the Sensemaking Machines

WIRED NextFest wrapped up in Chicago yesterday. If you missed it, you can still enjoy a catalog of innovations (PDF) that will make life more efficient, environmentally benign, and fun in the years to come.

With all the turmoil in the publishing industry, newspapers in particular, don’t be surprised at the absence of sleek, exciting presentations of text and graphic media.

But wait ’til next year – and hope. In the meantime, check out an interview by Curtis Brainard of the Columbia Journalism Review with Brad Stenger, research director of NextFest.

The interview is about the intersection of the press and computer science, and here are a few excerpts:

Stenger: Every news organization has an IT staff and one of the things that’s striking … [is] how the IT staffs are there to maintain infrastructure; they’re not necessarily there to deal with data and to generate insight about vast amounts of data. It’s a completely different skill set…

Brainard: What about interactive multimedia and graphics?

Stenger: … Where the computer science comes in, it’s not so much doing a one-off information graphic. That’s a practice that news organizations have done for decades, and for a lot of the interactive info graphics that go on Web sites, it’s the same sort of production pipeline. …[T]he essence of computational journalism [is] that you’re building tools that deal with streams of information. You deal with streams on the pre-production, research, reporting, newsgathering, sensemaking, insight-generating side of things, to develop news stories and find out where trends are going and what hasn’t been told to the public. And then once that’s done, there’s the final product, the public-facing side of the machinery—and once you’ve got something figured out, these sorts of machines can be built to run and run and run.

There is no shortage of prototypes for “machines” that make sense out of data. Edward Tufte’s seven books contain a wealth of examples, a classic being a comparison of graphics displaying cancer survival rates. What’s needed now is the investment in time and energy to use more of these valuable insights, more often, in more places.

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