Alfredo Covaleda,
Bogota, Colombia
Stephen Guerin,
Santa Fe, New Mexico, USA
James A. Trostle,
Trinity College, Hartford, Connecticut, USA
Here at the IAJ we believe one of the reasons people come to newspapers or broadcast stations is to get the data which, upon analysis, they can turn into information that helps them make decisions. Ergo, the more meaningful data a journalistic institution can provide, the greater value that institution has for a community. A good example arrived today thanks to Tara Calishain, creator of ResearchBuzz. She writes: ** Getcher Cheap Gas Prices on Google Maps <http://www.researchbuzz.org/getcher_cheap_gas_prices_on_google_maps.shtml> “Remember when I was saying that I would love a Gasbuddy / Google Maps mashups that showed cheap gas prices along a trip route? Turns out somebody has already done it — well, sorta. You can specify a state, city (only selected cities are available) and whether you're looking for regular or diesel fuel. Check it out at http://www.ahding.com/cheapgas/ “
The data driving the map is ginned up by GasBuddy.com It's not clear how or why GasBuddy gets its data, but it offers some story potential for journalists and data for news researchers. It has an interesting link to dynamic graphs of gas prices over time.
Surely the promotion department of some news organization could grab onto this tool, tweak it a bit, promote the hell out of it, and drive some traffic to and build loyalty for the organization's web site.
That's the obvious angle, but what if some enterprising journo started to ask some questions of the data underlying the map? What's the range in gas prices in our town/state? (In Albuquerque today, the range was from $2.04 to $2.28.) Are there any demographic or traffic flow match-ups to that price range? How 'bout the variance by brand?
Would readers appreciate this sort of data? We think so, especially if there was an online sign-up and the news provider would deliver the changing price info via e-mail or IM much like Travelocity tells us when airline ticket prices change by TK dollars.
Matt Ericson, the top-flight map/infographics journalist/designer at The New York Times, produced another fine piece of work Tuesday related to changes in the Roman Catholic world. But what we get in print is superior [click here to see IoP version] to the online version of the cartogram (i.e. proportional map), which illustrates how the church has grown in Latin America, Africa and Asia. The print page positions the RC world c. 1900 right next to the RC population c. 2005. Readers' eyes can quickly shift from one region to the other and see the differences. On the other hand, the online treatment of those graphics, while supplying data for three different eras — 1900, 1978, 2005 — bring up each era individually, making it difficult to compare one to the others. Snazzy presentation, but at a loss of comprehension. Go to NYT story “Third World Represeents a New Factor in Pope's Succession” and click on the right column link for “Interactive: After John Paul II.” Then, after the java window pops up, click on “Changes in Catholics.”
Xcelsius does magical things for your Excel spreadsheets. It turns the numeric data into controlable Flash charts, which can be standalone “movies,” imported into PowerPoint or sent to colleagues as click-and-manipulate e-mail. Check out the Quicktime demos at http://www.infommersion.com/demos.html
This Gallery of Data Visualization displays some examples of the Best and Worst of Statistical Graphics, with the view that the contrast may be useful, inform current practice, and provide some pointers to both historical and current work. We go from what is arguably the best statistical graphic ever drawn, to the current record-holder for the worst. See http://www.math.yorku.ca/SCS/Gallery/
It was in the early '90s, when JTJ began thinking about and researching the process that results in the journalist's product. It eventually boiled down to the RRAW-P process: Research–>Reporting–>Analysis–>Writing and finally Publishing/Producing/Packaging. The attached paper first appeared in the Social Science Computer Review in 1994.