Yesterday, we talked about Patch's new Divorce Maps, which show you where the divorced people in your town are congregating so that you can avoid those areas or, perhaps, start up specialty businesses that cater to divorcees.
Last night I heard from social scientist Eva Kaplan, who had an insightful comment about how these kinds of things get made. Here's her email:
I am a social scientist who works a lot with techies to understand how to better use data. I think what we have with divorce map is an interesting technical experiment with data that misses the relevance to, um, human beings. I see this all the time in my work. What Patch is trying to do is take national datasets and make them locally relevant. The problem is that there are not that many national datasets that can be geolocated, and so you get things like this-- one of the ironies with all the big data hype is that, despite the whole "data, data everywhere" thing, the gaps are still pretty basic and profound.
Divorce map, to me, is very typical example of a tech-driven use of data, rather than an editorial driven use of tech. It is interesting in a technical and conceptual sense, but should have stayed in the "lab" until there was an actual story to tell.