The Journalist’s Dashboard

(A Duke University) report suggests that journalists need “a tool with which to spot what’s new and what’s important in the flow of daily information.” A dashboard could include:

  • A news alert system similar to Google News that scanned only the sources specified by a beat reporter,identifying the originating publisher and the number of other sites that linked to the item;
  • A tool helping journalists keep track of their sources, including news items about that person and citations from the reporter’s own archived stories mentioning him or her;
  • A “trends and outliers” tool that might generate an alert any time a data source reveals a significant change in a piece of data — say, a surge in monthly expenditures by a government agency, or a flurry of crime reports in a short period of time.
  • A timeline generator that would display incidents related to a particular story as well as coverage on blogs and news sites.
  • An annotator that would allow a reporter to see past stories, images and contextual information while writing — for instance, by displaying background information about the person being written about.

I was watching a business news piece on TV this afternoon in which a reporter commented that she had recently interviewed a batch of Silicon Valley types who said they hoped their own kids would grow up to become statisticians. That, the techies opined, is where the jobs and the money are going to be in the future. The reason is because the Internet is causing a flood of information that no one has enough time or resources to sift through for significance.

So then I ran across this piece from PBS talking about the link between the future of journalism and technology, citing a Duke University study that called for development of tools to help journalists track trends, shifts and background information.

My first thought was, “Why not!?” These are exactly the sort of analytical and decision-support tools already in widespread use in other industries, particularly financial and intelligence. They are fed all manner of input and watch for changes from the norms or listen for keywords to crop up before alerting someone to the opportunity for human evaluation. So it is just a matter of vision and money to make such a system that has journalistic rather than other criteria at its core.

My second thought was that this was not a new idea, though perhaps it is more practical today than when we first explored it in the Gannett Newspaper Division’s Advanced Systems Lab back in the early 1990s. Back then, Bill Toner – who headed the Lab – had made a passing acquaintanceship with some people who had offices in similar outlying areas around Washington, DC, where Gannett had its headquarters at the time. These people apparently developed all sorts of interesting software to help various unnamed three-letter government agencies make sense of mountains of data, and a lunch conversation had turned to how regular businesses, particularly a newspaper, might use versions of such tools.

As a journalist and the only other member of the Advanced Systems Lab, I helped spec what such a black box might do in a newsroom. One of the ideas, for instance, was having it eat the city budget and spit out any statistically significant changes from past spending as a starting place for the local government reporter to begin asking questions. It was nothing that could not be done by one of the then-new breed of computer-assisted journalists. But those folks were rare at the time. The idea was that this black box might make those statistical capabilities available in every newsroom, plus make it a five-minute number crunching routine rather than the more typical weeks-long laborious effort.

Like a lot of projects in the Lab, this one never got much beyond early exploration. The newspaper recession of the mid-’90s arrived and the Lab was shut down as a cost-saving measure. Bill and I were spun off to work with newsroom digital archiving and mobile advertising sales, two of the Lab’s projects that had successfully transitioned from prototype systems to commercial products. I left instead to get back to real newsrooms and real journalism.

Then again, back in the mid-’90s, we were pushing up against the limits of what technology could do economically. Most city budgets were not even available in digital form at the time, for instance, so the first hurdle would have been getting and inputting enough raw material for such a news analysis system. Also computers were anything but cheap, user friendly (Macs notwithstanding) or standardized back then, so our prototype would have been much more expensive than simply training up a batch more computer-assisted journalists who could do a lot of other reporting as well.

Today, though, the technology has gotten pretty cheap, on top of the fact that we can now tie together huge resources through the Internet to tackle such journalistic analysis on a routine basis. And as those Silicon Valley moms and dads have noted, there is plenty of digital information today just begging for people to make sense of it. One might say it is not just a journalistic opportunity, but a journalistic mission.

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