A Memorial Day trip to Dallas included a visit to the Dallas Museum of Art to see an exhibit by On Kawara. On Kawara is probably most famous for his paintings of dates of significant events. (Warning: for the faint of art, Kawara is about as modern as you can get. In the art world it is termed “conceptualism”.)  But my fascination came from what I would term, “the art of OCD”.   He has, among other fascinating collections of… hand compiled data, manuscripts that detailed maps of his wanderings for an entire day, every day, from 1968 until 1979. This is 4740 pages. In the age of GPS and Google maps, this would still be a major feat. From the perspective of social geography, this is fascinating, especially if we Mashup with other geographic city data and/or other people. This is where CitySense comes in.

CitySense is a Mashup application created by Sense Networks:

Sense Networks, Inc. indexes the real world using real-time and historical location data for predictive analytics across multiple industries.

CitySense uses geographic data and real-time cell network data to track the movement of people (currently by opt-in cell phone location data) in San Francisco. Privacy issues aside, the application is impressive. Tracking the real-time flow of people across an urban landscape has applications in just about any social field.

So where does the science come in? One of my favorite researchers, Albert-Laszlo Barabasi, recently co-authored an article in the journal Nature, Understanding individual human mobility patterns. In this study, he and the other researchers were able to track 100,000 cellphone uses over the course of 6 months (in Europe, where privacy laws are… well, more realistic). They find:

After correcting for differences in travel distances and the inherent anisotropy of each trajectory, the individual travel patterns collapse into a single spatial probability distribution, indicating that, despite the diversity of their travel history, humans follow simple reproducible patterns.

Perhaps it’s not new news, and, in fact is somewhat predictable, but we now have evidence to say it is true, as well as means to begin manipulating the data and running scenarios. Barabasi has a fascinating and easy to read primer on network theory, Linked: How Everything Is Connected to Everything Else and What It Means.

I just love connections.