Transportation Techies Show What Can Be Done With Bike Data

How can you use data to explore biking?

The Transportation Techies Meetup group recently examined the possibilities. Five presentations at our first Bike Hack Night showed the range of what can be done with bike data.

Ironman Tim Kelley (also a Mobility Lab contributor) showed us how he uses Strava to visualize his bike trips. You’ve probably seen Strava’s global heatmap of millions of runs and bike rides, showing routes favored by its members. These routes tend to highlight training rides, since Strava members tend to be serious athletes. Thus, Hains Point in Washington D.C. is a popular route, even though the scenic route isn’t practical for bicycle commuters.

Tim can use Strava to make a cycling heatmap showing just his own history of bike rides. For specific rides, Strava has an Activity Playback tool that animates a group of cyclists riding together. There are also third-party applications that visualize Strava data. Before Strava changed its API features, VeloViewer was able to create animations of all Strava cyclists in a region. Tim used the tool to create a video called A Beautiful Weekend For a Bike Ride, showing 750 riders over a three-day weekend in April 2013.

For programmers interested in trail-counter data, Arlington is one of the first jurisdictions to offer an API to access data from its Bicycle & Pedestrian Counters. Sridevi Beidha from the Redmon Group showed us how the API works. The Data for Developers page has all the info you need to get started.

Another type of bike data is where the bike trails are. OpenStreetMap, the Wikipedia of maps, not only lets people access its data, it also lets people contribute trail data. Brian DeRocher showed us how it works. The OpenStreetMap data is used to power programs like OpenCycleMap. In fact, Brian was able to install an Open Source Routing Machine (OSRM) on his own server, showing how anyone can access the bike-route database.

Then there’s GPS ride art. David Pomeroy showed us how he turns the street-grid into a canvas, by planning bike trips with the goal of making GPS tracks that when viewed are drawings. Below is a 70-mile bike ride in the shape of a tyrannosaurus rex. You can find more examples at the BikeArlington Forum.

I presented a few of my own JavaScript apps that visualize bike data. The first problem was creating the perfect map of bike shops. One approach is to manually enter every known bike shop, like my Bike Shops and Beyond map for D.C. and Arlington, which also displays other places I thought were important to building good neighborhoods, like grocery stores, cupcake shops, and bowling alleys. But a manually “curated” map like this is limited to a small region, and it quickly becomes outdated. So another approach is to use an API from a robust database, like Yelp or Google Places. But my Yelp Mapper and Places Mapper reveal the limits of this method: bad matches, missing businesses, and limits to how many shops can be displayed at a time.

Municipal data offers more mapping opportunities. We talked about Analyzing DC Bicycle Theft Data, using five years of police data to create a mini animation. I also shared tools I created for showing bike data. The Stat Mapper has datasets for D.C. bike counts, D.C. bike crashes, Arlington bike crashes, and Arlington bike counts. The Activity Mapper attempts to show data from Arlington’s trail counters.

We also snuck in a visualization using Capital Bikeshare data. Joseph Owen showed us his Composite Visualization, which automatically groups CaBi stations based on usage patterns.

As biking becomes more popular, it’s good to use data to learn more about how people cycle in the city.

Know of any other cool bike-related apps or data visualizations? Let us know, and we’d love to see it at an upcoming Transportation Techies Meetup!

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