[Editor’s note: My colleague Sarah Cohen at The Washington Post was recently interviewed by Poynter about creating data visualizations to help readers understand and reporters research complicated stories. Sarah is on her way to a big new gig at Duke University.]
Readers have come to rely on interactive presentations to understand complicated stories, using them to zoom in on periods of time and highlight areas of interest. Yet to investigate these stories, reporters often create what amounts to handcrafted investigative art: flow charts with circles and arrows, maps shaded with highlighters and stuck with pins.
More and more, though, some reporters are using data visualization tools to find the story hidden in the data. Those tools help them discover patterns and focus their reporting on particular places and times. Many of the presentations, which can have rough interfaces or less-than-sleek design, are never published.
At the recent National Institute for Computer-Assisted Reporting (NICAR) conference, Sarah Cohen, database editor for The Washington Post‘s investigative team — and recently named professor of computational journalism at Duke University — showed how reporters can use interactive graphics for their exploratory reporting. [PDF]
Cohen described this approach to me via e-mail. Here’s an edited version of our exchange.
Steve Myers: How would creating a digital, visual representation of data help a reporter? What does it tell you that you wouldn’t be able to find otherwise?
Sarah Cohen: The same way that visualizations and graphics help readers cut through a lot of clutter and display dense information in an efficient way. The most common things that early visualizations help with are place and time — two of the most important elements in reporting a complex story. Those two things are really hard to see in text. They’re really, really hard to see in combination. So the graphics can show you where to go to find your subjects or where to go to find the most typical subjects. They can also show you when the story you are trying to find peaked. Put them together, and you can start finding the very best examples for your story.
That’s pretty general, so let me give you a couple of examples. During a story on disaster payments in the farm subsidy system, we wanted to make sure that we went to places that had received the payments year after year after year. Using a database, we could find farms that had received multiple payments pretty easily. But looking at repeated images of density maps that I made of the payments, it was really obvious where to go — specific areas of North Dakota and Kansas.
Sarah Cohen/Poynter illustration
Cohen used density maps to figure out what areas of the country had received disaster payments year after year.
In another example, we were working last year on a story on practices used by landlords to empty their buildings, partly in order to avoid strict laws on condo conversions (visualizations: research version, published version. We knew one neighborhood of the city was Ground Zero — an area called Columbia Heights, in Northwest D.C. But making an interactive map with a slider that showed the timing, we could see that it was moving into other areas of the city, especially in Southeast. We could also quickly see that the most affluent areas of the city had none of them.