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CAGIS Buildings to be Imported into OSM

Meanwhile in the world of OpenStreetMap, Minh Nguyen and I have been putting together a proposal for the import of CAGIS’s building footprint dataset which has been recently listed under a public domain license. This would add about 295,000 building footprints to OpenStreetMap in Hamilton County, many with address and height information. To any OSM contributors who may be perusing this blog, we’re still processing the data and could use all the help we can get once it comes time to actually do the import and especially when we need to get our hands dirty with some manual conflation. For the rest of you, map users, data consumers, etc, get ready for a more complete OSM in Cincinnati!

Post Script: For the especially keen, Minh has compiled a vast and surprisingly interesting summary of OSM completeness in the Cincinnati MSA (and Ohio).

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Posted in: Data | Maps
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Historical SORTA real-time data available

For the last few months I’ve been scraping SORTA’s real-time GTFS data for vehicle positions. I don’t really have any plans for what to do with all of it, but it’s easy for me to collect and I figure someone else may have a use for it somewhere down the road. This could eventually be a very interesting dataset for looking at e.g. changes in on-time performance, traffic congestion, bunching, etc.

Essentially, for each vehicle in operation at a given moment, I’ve been storing its:

The API updates all vehicle locations every 30 seconds and I’ve been requesting updates every 25 seconds and ignoring duplicates, so I should have all of the data on vehicle positions that have been made publicly available. I’ve tried to keep my script running steadily, but there have inevitably been a few interruptions as the postgresql server has been restarted, etc, so there may be some big gaps. Where there is any data, it should be complete; It just may skip out for a day or two. The earliest date I have is 2017-05-16 17:59:36.

Anyway, here is the script I’ve been using along with ancillary files:

SORTA data scraping script

and a compressed SQL dump of the PostGIS DB:

SORTA-historical-AVL.sql.7z

The script is still running, so if you find this post in a year, hit me up for some fresher data!

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Posted in: Data
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Historical vehicle location data

In case anyone is interested, I’ve begun storing data from SORTA’s GTFS-realtime feed. I started the script today and I see no reason to stop it unless I start running out of space on my server. I’ve got GTFS trip_id’s, vehicle_id’s, locations and timestamps for every vehicle location update from here until infinity.

Let me know in the comments if you happen to be interested and I’ll find a way to share the data!

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Posted in: Data
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Real-time display project funded!

I’m excited to announce that I’ll be spending part of this summer working with Daniel Schleith and Brad Thomas on a rather exciting project… Thanks to a grant from People’s Liberty, we’re going to have the opportunity to develop what I believe will be the first application to make use of SORTA’s recently released real-time data.

The goal of the project is to get real-time arrival displays into businesses along major transit lines. These will be privately owned and operated computer displays that ingest real-time data through the interwebs and display localized arrival predictions for nearby stops. We’ll be developing a display/app1, and subsidizing the purchase of tablet computers which can then be mounted behind a bar, in a shop window, near the door of the coffee shop, etc.

I’m sure I’ll have lots more to say here on the topic in the near future, but for now, I leave you with hope only.

Show 1 footnote

  1. F&OSS, of course.
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Posted in: Back to Basics
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SORTA’s Real-time API Now Available for Developers

Yep. It’s finally here! :-D

Vehicle location feed:
http://developer.go-metro.com/TMGTFSRealTimeWebService/vehicle
Trip update feed:
http://developer.go-metro.com/TMGTFSRealTimeWebService/TripUpdate

The data is structured according to the GTFS real-time specification. I was able to parse it pretty easily in Python by following the instructions on that page. The fields currently included in the feed (many are optional in the specification) are as follows.

VehicleLocation feed sample data:

id: "4001"
vehicle {
  trip {
    trip_id: "940867"
  }
  position {
    latitude: 39.1043395996
    longitude: -84.3908996582
  }
  timestamp: 1421889007
  vehicle {
    label: "4001"
  }
}
...

TripUpdate feed sample data:

id: "938755"
trip_update {
  trip {
    trip_id: "938755"
    start_time: "17:07:00"
    start_date: "20150121"
    route_id: "1"
  }
  stop_time_update {
    stop_sequence: 5
    departure {
      delay: 60
      time: 1421878357
    }
    stop_id: "EZZJOHe"
  }
...
  stop_time_update {
    stop_sequence: 32
    arrival {
      delay: 60
      time: 1421880000
    }
    stop_id: "PAR2610e"
  }
  vehicle {
    label: "1001"
  }
}
...

The feeds update every 30 seconds, which seems a little slow, but oh well.

Right now, my understanding is that these feeds have been tentatively released as-is for developers only, and that SORTA is not ready yet to make a general public announcement that real-time data is available. Tim Harrington at SORTA, who shared the links with us, has politely asked to see the neat stuff that we’re able to develop with this data. I imagine that the sooner someone sends him a link to a decent, working app, the sooner they’ll give us the go-ahead and the sooner we’ll all be able to use this data in every-day situations.

So who’s gonna make an app? There must be a dozen open-source applications that are already designed to work with GTFS-realtime. We probably just need to plug this feed in and maybe make a few localization tweaks. If you or anyone you know has the skills and/or interest to make an app…then for the love of transit, let’s make this happen ASAP!

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Posted in: Data | Events
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Foreshadowing

Mysterious Image…you should be able to guess what this is if you’ve been reading the blog lately. You should also then know why I’m very, very excited about it :-)

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Posted in: Events
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