Data Science, Analytics, and Visualization
Harnessing the potential of data science for world-changing social applications.
Research Projects
CAREER: API Can Code: Situating Computational Learning Opportunities in the Digital Lives of Students
Principal Investigator(s): David Weintrop
Funder: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization > Human-Computer Interaction > Youth Experience, Learning, and Digital Practices
Principal Investigator(s): David Weintrop
Funder: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization > Human-Computer Interaction > Youth Experience, Learning, and Digital Practices
Testbed for the Redlining Archives of California’s Exclusionary Spaces (T-RACES)
Principal Investigator(s): Richard Marciano
Research Areas: Archival Science > Data Science, Analytics, and Visualization > Library and Information Science > Machine Learning, AI, Computational Linguistics, and Information Retrieval
Making publicly accessible online documents relating to the practice of “redlining” neighborhoods in the 1930s and 1940s in eight California cities. “Redlining” refers to the practice of flagging minority neighborhoods as undesirable for home loans. The project creates a searchable database and interactive map interface.
Principal Investigator(s): Richard Marciano
Research Areas: Archival Science > Data Science, Analytics, and Visualization > Library and Information Science > Machine Learning, AI, Computational Linguistics, and Information Retrieval
Making publicly accessible online documents relating to the practice of “redlining” neighborhoods in the 1930s and 1940s in eight California cities. “Redlining” refers to the practice of flagging minority neighborhoods as undesirable for home loans. The project creates a searchable database and interactive map interface.
Computational Treatments to re-member the Legacy of Slavery (CT-LoS)
Principal Investigator(s): Richard Marciano
Research Areas: Archival Science > Data Science, Analytics, and Visualization > Information Justice, Human Rights, and Technology Ethics
Using Computational Archival Science to unlock records related to the Legacy of Slavery and provide new point of interaction and analysis.
Principal Investigator(s): Richard Marciano
Research Areas: Archival Science > Data Science, Analytics, and Visualization > Information Justice, Human Rights, and Technology Ethics
Using Computational Archival Science to unlock records related to the Legacy of Slavery and provide new point of interaction and analysis.
Faculty
Recent News
(Video) SoDa Symposium Seed Grant Series: “Do County Demographics Shape Exposure to Cyber Harm?”
Panelists discuss cybersecurity, cyber harm, federal funding programs, and more
(Video) Dean’s Lecture Series: Game-Changers: Unleashing the Power of Sports Informatics in Athletics
Panelists discuss the game changing unification of sports and data
Kevin Beverly