Data Science, Analytics, and Visualization
Harnessing the potential of data science for world-changing social applications.
Research Projects
When Does Encouraging Diverse Initial Solutions Lead to Better Final Solutions?
Principal Investigator(s): Joel Chan
Funder: National Science Foundation
Research Areas: Computational Linguistics, Machine Learning, and Information Retrieval > Data Science, Analytics, and Visualization
Designing high-performing engineering systems--for example, fuel-efficient aircraft, medical devices, new manufacturing and agricultural equipment--requires searching for high-quality solutions among many possible options.
Principal Investigator(s): Joel Chan
Funder: National Science Foundation
Research Areas: Computational Linguistics, Machine Learning, and Information Retrieval > Data Science, Analytics, and Visualization
Designing high-performing engineering systems--for example, fuel-efficient aircraft, medical devices, new manufacturing and agricultural equipment--requires searching for high-quality solutions among many possible options.
Digital Curation Fellows Program – National Agricultural Library
Principal Investigator(s): Katrina Fenlon
Funder: USDA Agricultural Research Service
Research Areas: Computational Archival Science > Data Science, Analytics, and Visualization > Library and Information Science
The Digital Curation Fellows program is a partnership with the National Agricultural Library (NAL) to provide students from across all iSchool programs with research and practical experience solving real-world digital curation challenges. Digital curation fellows have contributed to numerous initiatives during this program’s several-year history, such as developing digital preservation plans, researching user experience, evaluating metadata quality, assessing diversity and equity of representation in digital collections, building new digital archives, and creating data analytics dashboards.
Principal Investigator(s): Katrina Fenlon
Funder: USDA Agricultural Research Service
Research Areas: Computational Archival Science > Data Science, Analytics, and Visualization > Library and Information Science
The Digital Curation Fellows program is a partnership with the National Agricultural Library (NAL) to provide students from across all iSchool programs with research and practical experience solving real-world digital curation challenges. Digital curation fellows have contributed to numerous initiatives during this program’s several-year history, such as developing digital preservation plans, researching user experience, evaluating metadata quality, assessing diversity and equity of representation in digital collections, building new digital archives, and creating data analytics dashboards.
Maryland Sports Data Analytics Camps for Youth
Principal Investigator(s): Tamara Clegg
Funder: National Science Foundation
Research Areas: Accessibility and Inclusive Design > Data Science, Analytics, and Visualization > Youth Experience, Learning, and Digital Practices
Advancing knowledge of informal learning experiences that build adolescents' motivation for participation in STEM courses and careers, with a specific focus on introducing middle school African American and Latinx youth to the world of sports data analytics through events and summer camps.
Principal Investigator(s): Tamara Clegg
Funder: National Science Foundation
Research Areas: Accessibility and Inclusive Design > Data Science, Analytics, and Visualization > Youth Experience, Learning, and Digital Practices
Advancing knowledge of informal learning experiences that build adolescents' motivation for participation in STEM courses and careers, with a specific focus on introducing middle school African American and Latinx youth to the world of sports data analytics through events and summer camps.
Faculty
Recent News

Parkdale High School Students and UMD Team Up to Mitigate Local Flooding
A new partnership between INFO and ARCH will educate youth in critical data science and help them become environmental stewards.
Cracking the Privacy Code: Navigating the Condor Dataset while Safeguarding User Identities
A Q&A with INFO Assistant Professor Cody Buntain