NYC Open Data Leads to Parking Changes – An example for other agencies

tumblr_inline_n4kaea9Oki1szvr4hThe City of New York adopted an open data policy in 2012.  IQuantNY sifted through the newly open source data to find the highest grossing fire hydrant – $33,000 worth of parking fines per year at 152 Forsyth in Manhattan.  Just a block away, there was a $24k/year hydrant.  You can read about it here and here.

IQuantNY (Ben Wellington) took the innovative step of looking at google streetview at the locations and realized the hydrant was set back from the street and the markings on the street made it look like there were legal parking stalls adjacent to the hydrants.

The IQuantNY blog posts rose up through the reddit sites online to the point where this became a news story in the local paper.  Based on the news story, the NYC DOT went out to Forsyth Street within a couple of weeks and painted out the street to make it clear these were not parking stalls.

Problem solved – the street is staying clear so the fire department can access the hydrants (which is the point of the no parking, the point isn’t to generate ticket revenue).

IQuantNY was curious about something, had access to the data, and came up with a relevant thing that needed to happen to improve society – well done!  And the NYC DOT did a nice job of quickly fixing the  situation.

This is a small example of harnessing the public to improve society.  All agencies should adopt NYC’s open data policy.  We can’t imagine the improvements that could come from the data.  And as engineers, we should also try to ask interesting questions like this ourselves…..

Please note: I reserve the right to delete comments that are offensive or off-topic.

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2 thoughts on “NYC Open Data Leads to Parking Changes – An example for other agencies

  1. The simpler solution would have been for the people writing the tickets to say, “Hey, I write a lot of tickets here, maybe someone should improve the traffic markings.”

    Data is great, but better communication could have fixed the problem a lot easier.

  2. J,

    Agreed, but my experience is that the guys in the trenches don’t think at that macro level. Their busy on knocking out the task in front of them.

    The data mining should happen (ideally within the agency) to tease out these kinds of things.

    Mike