Some of you know I’ve written a fair bit on Google transit and how it is reshaping public transit – this blog post in particular comes to mind. For more reading I encourage you to check out the Xconomy article Google Transit: How (and Why) the Search Giant is Remapping Public Transportation as it provides a lot of good details as to what is going on in this space.
Two things about this article:
First, it really is a story about how the secret sauce for success is combining open data with a common standard across jurisdictions. The fact that the General Transit Feed Specification (a structured way of sharing transit schedules) is used by over 400 transit authorities around the world has helped spur a ton of other innovations.
Couple of money quotes include this one about the initial reluctance of some authorities to share their data for free (I’m looking at you Translink board):
“I have watched transit agencies try to monetize schedules for years and nobody has been successful,” he says. “Markets like the MTA and the D.C. Metro fought sharing this data for a very long time, and it seems to me that there was a lot of fallout from that with their riders. This is not our data to hoard—that’s my bottom line.”
and this one about iBart, an app that uses the GTFS to power an app for planning transit trips:
in its home city, San Francisco, the startup’s app continues to win more users: about 3 percent of all trips taken on BART begin with a query on iBART
3%? That is amazing. Last year my home town of Vancouver’s transit authority, Translink, had 211.3 million trips. If the iBart app were ported to here and enjoyed similar success that would man 6.4 million trips planned on iBart (or iTranslink?). That’s a lot of trips made easier to plan.
The second thing I encourage you to think about…
Where else could this model be recreated? What’s the data set, where is the demand from the public, and what is the company or organization that can fulfill the role of google to give it scale. I’d love to hear thoughts.
Has anyone used this data to try and suggest optimizations? That seems like an obvious next step.