Nieman Foundation at Harvard
Participants at Matt Thompson’s recent gathering on the Future of Context discussed (among many other things) database journalism — city crime maps, for example — and agreed that they can actually be a disservice to readers. The problem comes in maintaining the data: a reporter or team gathers data, analyzes it, creates interesting presentation graphics — and then often fails to maintain the data, so that it is quickly out of date, irrelevant, and even misleading. As well, a map presented without context or interpretation can lead to erroneous conclusions by readers.
As news organizations look to add high-value content that might form the core of paid-content sections for their sites, compilations and analysis of public (but not necessarily online) information is one of the areas they’re exploring. (See, for example, Steve Buttry’s laundry list of data the Cedar Rapids Gazette is looking to incorporate on its sites.) As the data imported to the site grows, so does the maintenance issue.
One way out of this is the way the Raleign (N.C.) News & Observer handles it: their crime maps are set up to pull information directly and continuously from law enforcement databases, so that the maps are always up-to-date. The N&O uses the same approach with many of the other data topics in its impressive Fact Finder resource.
Another resource that may prove useful to database journalism is Wolfram Alpha, which is set to launch on May 18. Some have heralded its advent as potentially “changing the internet forever”:
Wolfram Alpha will not only give a straight answer to questions such as “how high is Mount Everest?”, but it will also produce a neat page of related information — all properly sourced — such as geographical location and nearby towns, and other mountains, complete with graphs and charts.
The real innovation, however, is in its ability to work things out “on the fly,” according to its British inventor, Dr. Stephen Wolfram. If you ask it to compare the height of Mount Everest to the length of the Golden Gate Bridge, it will tell you. Or ask what the weather was like in London on the day John F. Kennedy was assassinated, it will cross-check and provide the answer. Ask it about D sharp major, it will play the scale. Type in “10 flips for four heads” and it will guess that you need to know the probability of coin-tossing. If you want to know when the next solar eclipse over Chicago is, or the exact current location of the International Space Station, it can work it out.
To get a better sense of what Wolfram Alpha does, have a look at its inventor, Dr. Stephen Wolfram, demonstrating a series of queries to the system.
(Or if you’ve got a couple of hours, tune in to his full presentation at Harvard’s Berkman Center recently.)
With up to 1,000 participating experts “curating” the information pulled into Wolfram Alpha, it’s likely to be a powerful tool. (Although I can’t speak from experience — so far I’ve had no luck getting a press pass for a sneak preview.)
So one hopes that Dr. Wolfram’s project will turn out to be a powerful tool for journalists, as well as for the public. The caveat is, however, that it’s one thing to download a lot of data, and something else to make sense of it. Wolfram Alpha appears to generate graphs that show trends and relationships, but it won’t create meaning. (At least, not yet.)
Making sense of data often requires mathematical skills, and when hiring at news organizations, we usually look more closely at candidates’ ability to write a sentence in English than at their talent with numbers. (During my career as publisher, reporters and editors often popped in to ask me which number to divide into which to compute a percentage, or where a decimal point should go.)
So news organizations building database resource platforms, whether local or global, should consider these factors:
