NYC VERTICES:

In several recent posts, I’ve talked about experiments with personal geographic data collected via OpenPaths. In those examples, location is treated in absolute terms, latitude and longitude.

However, I am working toward something here. Most of my past work has been concerned with the relative qualities of place, the psychogeography that isn’t necessarily keyable to coordinates (see our article in Urban Omnibus). Presently, I’m developing some analytics to try and bridge that gap.

The first order of business is to begin thinking about location in terms of place. Place is a concept that is relative to the context of the individual — but using geodata we can at least identify significant patterns that suggest loci of activity.

Starting from my path data, I used a clustering algorithm (I’ll post the code next) to construct a network graph of my arrivals and departures around the city. What you see here are the locations of all of my “significant” places around the city, over the last 6 months or so. NYT Labs is the big green point up top — home is purple toward the bottom. The lines show the strength of the connections between them (eg, from home I’m most likely to go to the lab).

The conceptual shift here, and I think it’s an important one, is to begin to treat location as behavior. More to come.

(drawn with python)