OpenText Data Digest Oct 2: Traffic and Public Transit
Despite constant congestion, data scientists are always coming up with ways to analyze traffic patterns to ensure you get to your desk by 9 a.m. Whether your transportation is trains or cars, we’ve got you covered, this week.
Does getting to work on Monday feel like a breeze or miles and miles of bad road? The average worker in the United States spends 200 hours at a cost of $2,600 a year on commuting, according to recent polls. Despite constant congestion, data scientists are always coming up with ways to analyze traffic patterns to ensure you get to your desk by 9 a.m. Whether your transportation is trains or cars, we’ve got you covered, this week. We’ve assembled three very innovative ways of showing and analyzing transportation data. Enjoy!
Big Data on the MTA:
Well, let me tell you of the story of a man named Charlie
On a tragic and fateful day
He put ten cents in his pocket, kissed his wife and family
Went to ride on the MTA
The ballad made famous by the Kingston Trio’s song MTA (commonly known as Charlie on the MTA) reminds us that transit can be a real nightmare for some and a treasure trove for others.
MIT electrical engineering and computer science Ian Reynolds boarded the train to data central with this homemade live data visualization. Taking GPS data from Boston’s own transit agency, Reynolds recreated the track system using Adafruit NeoPixel strips driven by an Arduino Uno, which in turn takes orders from a Python script running on a Raspberry Pi.
“Every ten seconds or so, it calls the MBTA API to grab the GPS coordinates of all the trains in the system. It maps those to some LEDs, decides which ones actually need to be changed, and then sends that information to the Arduino, which does the bit pushing,” Reynolds wrote in his description.
His next step is writing an app that lets him change the visualization and adjust the brightness. Reynolds posted his project on GitHub if you want to get under the hood. We’re just hoping this type of visualization helps Charlie get to Jamaica Plain once and for all.
Keep Calm and Visualize the Traffic Data: Of course, using data to alleviate traffic problems is not new. In the 60s and 70s, the British government often positioned workers with clipboards to tally the number of cars and the various types that passed through intersections. Decades later, traffic data was computerized onto a 2-dimensional map, which showed various hotspots at selected intervals.
In 2009, Jer Thorp (@blprnt) and a team of engineers saw a need to better represent the data in an interactive way. Their presentation entitled “Visualising Transport Data for data.gov.uk, [itoworld.blogspot.com] by ITO” was based on the traffic count data for data.gov.uk Developer Camp. The team used more than 1,000 existing data sets from seven departments and community resources.
The visualizations and resulting maps were built in nearly two days. The accompanying movies that document the presentation of the project are available as well as the resulting maps at Flickr.
Go With The Flow: Monitoring traffic flows is also helpful for retailers. Kirkland, Washington-based INRIX provided a proof of concept recently showed the migration of billions of anonymous data points from GPS or mobile networks.
The data visualization showed anonymous data flowing in and around Manchester, UK during a popular time for school shopping. The map revealed the local migration from the suburbs to shopping areas in Trafford Centre and Manchester City Centre. Their analysis revealed that much of traffic into the city was coming from the south.
The novelty of the visualization is not only showing the traffic patterns but also growing on a horizontal plane, the growing number of people in the city itself. The company said its data could be used by marketers, retailers and civic offices to keep people moving and market to specific demographics based on destinations.
Reviews of the project are available at the Silicon.de site (in German).
Like what you see? Every Friday we share great data visualizations and embedded analytics. If you have a favorite or trending example, tell us: Submit ideas to firstname.lastname@example.org or add a comment below. Subscribe (at left) and we’ll email you when new entries are posted.
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