UMD Data Challenge Integrates Communities with Data Science

By Dan Novak / Mar 29, 2019 / Updated May 1, 2020

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UMD Data Challenge

The 2019 Data Challenge cohosted by MAPP and the College of Information Studies (iSchool) took place February 23 with over 150 undergraduate and graduate students from various schools across campus and, for the first time, included a team from the U.S. Naval Academy.

The annual Data Challenge is a weeklong event that engages students, researchers and industry experts in exploring data integration for social good. The student team from the iSchool won this year’s grand prize for their innovative analysis and excellent presentation on real-time train prediction for WMATA—the Washington Metropolitan Area Transit Authority. The Data Challenge is one of the seven data science projects organized by MAPP and the iSchool and is funded by the Year of Data Science, a campus-wide initiative to promote data science at the University of Maryland. This event was organized with the open-ended theme of “Data Integration and the Community” to integrate technologists, social scientists and community-engaged researchers, as well as students from diverse disciplines.

Students worked on 15 different projects that included topics like public transit service, bike sharing services, crime, business, health and food security. Mentors were assigned to each of the 15 student teams to help formulate research questions, streamline the project process and provide suggestions for innovative data analytics and effective data visualization. Teams consisting of students from multiple disciplines learned from each other to gain practical and multidisciplinary experience.

MAPP has long been engaged in multidisciplinary, team-based collaboration important in addressing complex economic, social and environmental problems. With the emerging research frontiers in smart city and urban informatics, MAPP has started to expand its current research and education to take advantage of data science—a powerful tool underpinning much multidisciplinary research.

You can read more about the Data Challenge program and this year’s winners.