CSAIL's Big Data Initiative recently worked with city officials in Boston to highlight transportation issues by enlisting students in a competition. Read about this in the March 5, 2014 article "BIG DATA FOR BOSTON: TO IMPROVE TRANSPORT, CITY ENLISTS MIT STUDENTS TO CRUNCH NUMBERS" by CSAIL writer Adam Conner-Simons. Link to full article.
What happens when you give a bunch of MIT students GPS information on more than 2.3 million Boston taxi rides, and then offer them a cash prize to get creative with the data?
That was the idea behind the inaugural MIT Big Data Challenge organized by the MIT Big Data Initiative at CSAIL in partnership with the City of Boston and Transportation@MIT.
With urban congestion on the rise, planners have been looking for new ways to understand and improve transportation in Boston, which spurred the decision to collaborate with MIT and make available data from local events, Tweets, weather records and taxi rides in commercial zones of the city.
“We believe that big data can be used in the service of big issues,” said Elizabeth Bruce, Director of the MIT Big Data Initiative at CSAIL. “We thought it would be exciting to organize a challenge in which our community of students and researchers put their energies into tackling a tangible public-policy issue like transportation, and to see what insights emerge from that."
Since November, more than 250 teams submitted work focused on trying to predict demand for taxis and create intuitive visualizations about these topics. Among the questions that teams explored:
- where are the most popular taxi pick-up spots in Boston?
- how do taxi-hailing patterns change day-to-day and hour-to-hour?
- which common cab trips would actually be faster by bike?
At the final event February 27, teams presented their work and heard from a panel of judges that included the City of Boston’s director of transportation planning, Vineet Gupta.
“We are excited about this partnership with MIT because it opens up a whole host of opportunities for the city,” said Gupta. “The data analysis that these students have done reflects true out-of-the-box thinking, and has the potential to directly inform future policy decisions in Boston.”
Teams took first prizes for prediction and visualizations, respectively. The prediction winner was Suma Desu, a master's student at the Human Mobility and Networks Lab. The visualization winner was CSAIL graduate student Gartheeban Ganeshapillai, who created an interactive map that allows users to see how taxi patterns change over time. He also built a visualization that displays the most common intracity rides. (The winner, with over 10,000 rides, is the trip between Hynes Convention Center and the Cutler Majestic Theatre.)
Read the Full story on the CSAIL website: http://www.csail.mit.edu/node/2177