Visualizing New York’s Transit Data: MTA Track Fires

We examined MTA data collected around fires on subway tracks and the VacTrak cleaning schedules.

We looked at the frequency with which fires took place, and attempted to identify possible causes. A known cause of fires is trash on the tracks, so one area of particular interest was how often cleaning took place (with Vacuum Trains). Data examined included: the total number of monthly fires across the whole subway system, Vacuum Train activity (across one line), and delays during morning rush hour (also on one line only).

Along with the visualizations themselves, we delivered an interactive iPad prototype which afforded the MTA team a chance to see how the visualizations might be used in the context of board meetings.

Our hunch was that stations with more frequent vacuuming would see less fires, since less trash would be left on the tracks. Unfortunately, the very limited data set did not conclusively support this. However, the visualizations set up a language and format where identifying such connections would be possible, as well direction on where else to look for possible causes—and were very well received by the MTA team. Here was our presentation. And to read an overview of the 4-week SVA MFA Interaction Design and MTA Big Data workshop refer to this post.

In collaboration with Sam Wander and Hanna Yoon