Tag: Hack Night

Talking about Divvy data with WBEZ’s Afternoon Shift

Audio from 3-4 PM segment. Skip to ~30 minutes in to hear the data portion of the show. 

WBEZ Afternoon Shift host Charlie Meyerson had me on the show Monday to talk with him, Gabe Klein, and some fellows at Data Science for Social Good (DSSG, a University of Chicago-based program) about the trends that Divvy bike sharing data is showing. Here are trends I mentioned or was prepared to mention:

* 31 stations installed since Friday, July 19 (10 days since Monday, July 29), 28 stations installed since I wrote my post on Streetsblog Chicago about 67 memberships per day, so I predict that the daily rate of new annual members has increased.

* Membership enrollment is still concerning to me: From July 22 (when I wrote my post about enrollment rate) to yesterday (Sunday, July 28), membership enrollment rate dropped to 61 memberships per day, even as all these new neighborhood stations emerged. This brings the post-launch average to 66 from 67.

* If you look at Top 10 starting and ending stations, there’s about 90% crossover, meaning the Top 10 starting stations for trips are basically the same as the Top 10 ending stations. There’re slight changes on the weekend, with Lincoln Park (the park) and the Lincoln Park Zoo getting into the Top 10. (See table below.)

* During the week, Union and Ogilvie Metra stations get into the Top 10, and disappear from the Top 10 on the weekend. This may suggest that commuters, not tourists, are making these trips. But people make tourism trips from the suburbs on weekdays as well.

* Trips by member type: 71% are taken by 24 hour pass holders. This is down from 75 to 73, so this means that the share of trips taken by annual member holders is increasing. This is because of two things happening: some people who bought a 24-hour pass to test the system have converted to being an annual member, and others who waited for a station to come to their neighborhood have bought a membership. I’m just hoping that membership enrollment picks up to reach the high rate of installations.

I’m personally interested in the route data. I’m interested in who’s biking where and when. This is information we’ve not collected well in the past. My Streetsblog Chicago partner John Greenfield wrote about other data trends Scott Kubly discussed at last week’s Complete Streets Symposium.

Dock surfing during a Divvy social ride last Thursday. Photo by Jane Healy.

[table id=9 /]

Download this data

Divvy data from May 29 to July 28 (.xls): includes member enrollment, number of trips taken by annual and 24-hour pass holders, and top 10 starting and ending stations.

If you’re looking to contribute your expertise to the “Divvy data project” (okay, such a thing doesn’t really exist), then check out the Divvy Data Document I started after discussing Divvy data at a July OpenGov Hack Night.

BikeSpike has major potential impact for data collection

This is a pretty hilarious video showing the main reason one would get a BikeSpike: to catch a thief. 

Bill Fienup emailed me in December or January asking to meet up to talk about their bike theft tracking device (that does a whole lot of other stuff) but I couldn’t meet until February as the transition from Grid Chicago to Streetsblog Chicago was occupying my brain time. Bill’s part of Team BikeSpike.

The BikeSpike in hand. It’s very small and weighs 3.1 ounces.

It was convenient that they were at 1871 on a Tuesday night; I was there for Hack Night, they for one of the other myriad events that occurs on the 12th floor of the Merchandise Mart. They showed me a 3D-printed mockup of the BikeSpike, and told me what it was capable of doing. They seem to have a good programmer on their team in Josh Billions – yes, that’s his real last name.

I came to their lab near Union Park to talk in depth about BikeSpike with Bill, Josh, Harvey Moon, and Clay Neigher, garner more information, and provide them with some more insight into how the product can be useful to the transportation planning work I do as a Streetsblogger, advocate, and programmer. I brought my friend Brandon Gobel and he became interested to hear about how it could help him manage the future fleet of Bullitt cargo bikes he’s now selling and renting at Ciclo Urbano.

Beside the fact that BikeSpike can show law enforcement workers the EXACT LOCATION OF STOLEN PROPERTY, I like its data collection aspects. Like many apps for iOS (including Moves and Google Latitude), BikeSpike can report its location constantly, creating opportunities for individuals to track training rides and urban planners to see where people ride bikes.

Cities should know where people are riding so they can build infrastructure in those places! Many cities don’t know this until they either count them frequently and in diverse locations, or when they ask. But neither of these methods are as accurate as hundreds, or thousands of people reporting (anonymously) where they ride. I’ve got three examples below.

I imagine the BikeSpike will produce a map like this, which was created by Google Latitude constantly tracking me. 

Team BikeSpike: Clay, Bill, Ben Turner (I didn’t meet him), Josh, and Harvey.

1. Want to see if that new buffered bike lane on South Chicago Avenue actually encourages people to ride there and wasn’t just an extra-space-opportunity? Look at BikeSpike data.

2. The number of people biking on Kinzie Street shot up after a protected bike lane was installed. How many of these new Kinzie riders switched from parallel streets and how many were new to biking? Look at BikeSpike data.

3. Given relatively proximal origins and relatively proximal destinations, will people bike on a buffered bike lane (say Franklin Street or Wabash Avenue) over a protected bike lane (say Dearborn Street)? Look at BikeSpike data.

There are many other things BikeSpike can do with its GPS and accelerometer, including detect if your bike was wiggled or you’ve crashed. I want a BikeSpike but you’ll have to back the project on Kickstarter before I can get one! They need $135,000 more pledged by April 9.

Slicing the crash data into interesting visualizations

The Chicago Crash Browser as it looks now. This only exists on my laptop and no place else. I can’t put it online because it’s so inefficient it would kill the server. 

I presented my Chicago Crash Browser to attendees of an OpenGov Hack Night three weeks ago and gathered a lot of feedback and some interest from designers and programmers there.

We collaboratively came up with a new direction: instead of focusing on creating a huge web application that I proposed, we (anyone who wants to help) would start small with a website and a couple of crash data visualizations. The visualizations would serve two purposes:

  • attract attention to the project
  • start building a gallery of data-oriented graphics that describes the breadth and extent of the crash data

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