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[from Fernanda Viégas at Infovis'07]
Information visualization for lay users seems to be a pervasive theme at the InfoVis conference this year. Matthew Ericson, Deputy Graphics Director at The New York Times, gave a keynote entitled: "Visualizing Data for the Masses: Information Graphics at The New York Times".

He explained how a 30-person team creates the impressive infographics and visualizations we see on the newspaper every week. Matt emphasized their role as journalists (instead of illustrators) and explained how they get from raw data to finished graphical pieces that make information understandable for more than a million readers.

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[link: ericson.net (infovis presentation slides, ZIP format, 70mb)]

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I was happy to hear Matt talking about some of the intricacies of bringing visualization to "the masses." For instance, he mentioned how certain visualization techniques that are favored by the scientific community actually do not work well for lay users. Premier in this category was the scatterplot. That's right, good ol' scatterplots are not used by the NY Times because readers simply can't make sense of them (a lot of people expect to see time on the x-axis.)

The other takeaway from Matt's talk was his emphasis on the importance of textual explanations on infographics. His team always creates callouts and headlines explaining the most important points shown on the visualizations/graphics. By guiding readers' attention, these explanations and short stories create important entry points into the visualizations.

Bonus material: one of the coolest moments in the talk was the meet the entire NY Times graphics team in Simpsons style (see image below, Matt is on the top row, fifth from the left).
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1 COMMENT

sounds like a terrific presentation, I wish I had Matt's notes when viewing it! speaking of scatterplot, I like very much what they did on 38. It works much better to use a full page to show a big scatterplot, then 4 smaller "views" of it emphasing on one part of the graph, than trying to cram everything on one graph. Result: a scatterplot that works.
I also like what they've done in the 69-77 section about "honest maps". even reputable data publishers present maps which are most often biased.
the last graph I liked very much is the one on p94. when composing a graph the natural trend is to chose a scale so all the data points fit. here, doing the opposite and letting the WWII numbers break lose is very effective, "à la Al Gore". thanks for sharing.

btw, in the wake of the movie there are plenty of simpson avatar generators for you to try :)
-jerome

Tue 30 Oct 2007 at 5:19 AM
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