Mapping Habitual Geographies

by The New York Times R&D Lab

The Research and Development Lab at the New York Times is developing algorithms that identify and map the places we visit every day.

Each day we visit our habitual places, including where we live, where we work, where we shop, and where we relax. At the R&D lab, we are interested in creating maps of how people move between these places in New York and other cities. We hope to gain insight into how individuals structure their day around geography, which could inform future prototypes of location-based services and interfaces. Our mirror project ( is one example of an interface that might visualize location information based on methods developed with OpenPaths data.

The core component of this research is to develop an algorithm that can identify when individuals are moving between places and the strength of the connection between those places. A visualization that demonstrates a proof-of-concept for this algorithm can be seen here:

Mapping Habitual Geographies will create maps like the above from the data of each participant that contributes to the project. The data will help us to refine a robust means of producing meaningful maps from a diverse set of behavior patterns. We will then attempt to algorithmically find groups of similar-looking maps and see if we can define a taxonomy of places in the city.

The research described above will take place locally on a password-protected computer behind our corporate firewall. We will set up the project such that there will never be a reason to copy or transit the data off of this machine.

Though we hope that Mapping Habitual Geographies might result in an academic paper, the primary outcome will be improving the methods we use to look at geographic data. Since we also develop OpenPaths itself, we will apply our findings to the OpenPaths platform and integrate new types of maps, visualizations, and mobile services.