Research Projects
Systematically Documenting New Sociotechnical Foundations for Research Synthesis Infrastructures
Principal Investigator(s):
Funder: Alfred P. Sloan Foundation Other
Principal Investigator(s):
Funder: Alfred P. Sloan Foundation Other
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
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
The PROMISE Academy
Principal Investigator(s):
Funder: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization
Providing new college students with the necessary tools for success through intensive first level developmental courses, tutoring, advising, and the creation of learning communities comprised of faculty, staff, tutors, and advisors.
Principal Investigator(s):
Funder: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization
Providing new college students with the necessary tools for success through intensive first level developmental courses, tutoring, advising, and the creation of learning communities comprised of faculty, staff, tutors, and advisors.
Theory of Change Through Data
Principal Investigator(s): Wayne G. Lutters
Funder: New York University Other
Research Areas: Future of Work > Human-Computer Interaction > Library and Information Science
The Democratizing Data project supports federal agencies in understanding how their data assets are being used. Novel machine learning algorithms interrogate over 90 million publications to identify data usage, which is presented via a search and discovery platform with three interaction styles: interactive dashboards, Jupyter Notebooks, or direct API.
Principal Investigator(s): Wayne G. Lutters
Funder: New York University Other
Research Areas: Future of Work > Human-Computer Interaction > Library and Information Science
The Democratizing Data project supports federal agencies in understanding how their data assets are being used. Novel machine learning algorithms interrogate over 90 million publications to identify data usage, which is presented via a search and discovery platform with three interaction styles: interactive dashboards, Jupyter Notebooks, or direct API.
UMD Break Through Tech
Principal Investigator(s):
Funder: Cornell University Other
Research Areas: Future of Work
Principal Investigator(s):
Funder: Cornell University Other
Research Areas: Future of Work
WIN: a Window Into Neuroregulation
Principal Investigator(s): Richard Marciano Greg Jansen
Funder: National Science Foundation
Research Areas: Archival Science > Data Science, Analytics, and Visualization > Youth Experience, Learning, and Digital Practices
Creating technology and best practices for conducting science that is situated in the classroom setting with the purpose of better understanding children's ability to self-regulate when presented with challenges, which seem to be ever-increasing in our digital era society.
Principal Investigator(s): Richard Marciano Greg Jansen
Funder: National Science Foundation
Research Areas: Archival Science > Data Science, Analytics, and Visualization > Youth Experience, Learning, and Digital Practices
Creating technology and best practices for conducting science that is situated in the classroom setting with the purpose of better understanding children's ability to self-regulate when presented with challenges, which seem to be ever-increasing in our digital era society.