Transit agencies have long used intelligent systems for scheduling and monitoring the location of their vehicles. However, this real-time information had previously been available only to engineers inside agencies, leaving riders with printed timetables and maps that, at best, represent the stated intentions of a complex system that can be disturbed by traffic, weather, personnel issues and even riders themselves.

Recognizing the need for access to this information on-the-go and in digital format,

of Portland’s

agency worked with Google in 2006 to integrate timetable data into Google Maps, eventually becoming

. McHugh went further, publicly releasing TriMet’s operations data: first the static timetables, and eventually real-time, dynamic data feeds of vehicle locations and arrival predictions. Local programmers have responded with great ingenuity, building 44 different

for the TriMet system, at no cost to the agency.

Other transit agencies have adopted this

approach with varying outcomes. The most successful agencies work closely with local programmers to understand which data is in demand, troubleshoot and improve the quality of the data feeds. Programmers also make the link between end users and transit agencies by filtering up comments from app users. This iterative feedback loop relies on a champion within the agency to build strong relationships with the local developer community. Of the five transit agencies we studied, Portland’s TriMet and Boston’s

exemplify this approach and have generated the highest ratio of apps per transit rider (see table). Meanwhile, the most reluctant agency to adopt open data, Washington DC’s

, only had 11 apps serving its

in 2011.

Table: Transit Apps and Ridership by City