Inactive Research Projects
Information Technology Access RERC (Year 2)
Principal Investigator(s): J. Bern Jordan
Funders: Health and Human Services
Principal Investigator(s): J. Bern Jordan
Funders: Health and Human Services
Integrating Computing into Urban Elementary Mathematics Classrooms as a Means to Bring Computational Thinking to All
Principal Investigator(s): David Weintrop
Funders: National Academy of Education Other Non-Federal
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval Youth Experience, Learning, and Digital Practices
Principal Investigator(s): David Weintrop
Funders: National Academy of Education Other Non-Federal
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval Youth Experience, Learning, and Digital Practices
Integrating Immigrants Into the LIS Workforce: A Pilot, Collaborative Project
Principal Investigator(s): Ana Ndumu
Funders: Association for Library and Information Science Education (ALISE) Other Non-Federal
Research Areas: Information Justice, Human Rights, and Technology Ethics Library and Information Science
Introducing refugees and immigrants to library professions through a self-paced mini-course as part of a one-year pilot in partnership with the REFORMA Mid-Atlantic Chapter and Prince George’s Public Library System.
Principal Investigator(s): Ana Ndumu
Funders: Association for Library and Information Science Education (ALISE) Other Non-Federal
Research Areas: Information Justice, Human Rights, and Technology Ethics Library and Information Science
Introducing refugees and immigrants to library professions through a self-paced mini-course as part of a one-year pilot in partnership with the REFORMA Mid-Atlantic Chapter and Prince George’s Public Library System.
Integrative Visual and Computational Exploratory Analysis of Genomics Data
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval Data Science, Analytics, and Visualization Future of Work
Integrative visual and computational exploratory analysis of genomics data High-throughput genomics is now shifting from a data generation field to a data analysis field. Rapid advances in sequencing technologies and their use in large consortium projects like Encode, 1000 genomes project and the Human Epigenome Roadmap, among others, hold promise for biomedical scientists to posit and test hypothesis on complex mechanisms of development and disease by integrating massive publicly available data as context for their own experimental data.
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval Data Science, Analytics, and Visualization Future of Work
Integrative visual and computational exploratory analysis of genomics data High-throughput genomics is now shifting from a data generation field to a data analysis field. Rapid advances in sequencing technologies and their use in large consortium projects like Encode, 1000 genomes project and the Human Epigenome Roadmap, among others, hold promise for biomedical scientists to posit and test hypothesis on complex mechanisms of development and disease by integrating massive publicly available data as context for their own experimental data.
Internships to Increase Public Access to Archival Resources in National Capital Region Parks
Research Areas: Digital Humanities Human-Computer Interaction
Collaborating with the National Park Service to create an internship program in which students learn about existing archival resources as well as assist in developing and implementing a strategy to locate, identify, and survey archival records throughout National Capital Region parks.
Research Areas: Digital Humanities Human-Computer Interaction
Collaborating with the National Park Service to create an internship program in which students learn about existing archival resources as well as assist in developing and implementing a strategy to locate, identify, and survey archival records throughout National Capital Region parks.
Inverting Colonial Archival Structures: Increasing Discovery and Access for Indigenous Communities through SNAC
Principal Investigator(s): Diana E. Marsh
Funders: Institute of Museum and Library Services
Research Areas: Accessibility and Inclusive Design Archival Science Digital Humanities Library and Information Science Social Networks, Online Communities, and Social Media
This project aims to test discovery and access of archival records for indigenous communities through the web platform Social Networks for Archival Contexts (SNAC).
Principal Investigator(s): Diana E. Marsh
Funders: Institute of Museum and Library Services
Research Areas: Accessibility and Inclusive Design Archival Science Digital Humanities Library and Information Science Social Networks, Online Communities, and Social Media
This project aims to test discovery and access of archival records for indigenous communities through the web platform Social Networks for Archival Contexts (SNAC).
IRCN-CAS: International Research Collaboration in Computational Archival Science
Principal Investigator(s): Richard Marciano
Funders: Arts and Humanities Research Council (AHRC) Other Non-Federal
Research Areas: Archival Science Digital Humanities Library and Information Science
King’s College London’s Department of Digital Humanities, together with the University of Maryland iSchool Digital Curation Innovation Center (US), the Maryland State Archives (US), and The National Archives (UK), were awarded a 1-year International Research Networking grant for UK-US Collaborations in Digital Scholarship in Cultural Institutions.
Principal Investigator(s): Richard Marciano
Funders: Arts and Humanities Research Council (AHRC) Other Non-Federal
Research Areas: Archival Science Digital Humanities Library and Information Science
King’s College London’s Department of Digital Humanities, together with the University of Maryland iSchool Digital Curation Innovation Center (US), the Maryland State Archives (US), and The National Archives (UK), were awarded a 1-year International Research Networking grant for UK-US Collaborations in Digital Scholarship in Cultural Institutions.
Library Knowledge Extensions (KNEXT): Data Analytics to Support Innovation Communities
Principal Investigator(s): Susan Winter Andrew Fellows
Funders: Institute of Museum and Library Services
Research Areas: Data Science, Analytics, and Visualization Library and Information Science
KNEXT is a three-year collaborative project between Kent State University (KSU-SLIS) and the University of Maryland (UMD-CIS), which partners with local public libraries, small business development centers, economic development organizations, and community advocacy groups to bring advanced data analytics and business intelligence (DA&BI) services to public libraries in order to support small businesses, entrepreneurs, and community advocates within two recovering communities in Ohio and Maryland.
Principal Investigator(s): Susan Winter Andrew Fellows
Funders: Institute of Museum and Library Services
Research Areas: Data Science, Analytics, and Visualization Library and Information Science
KNEXT is a three-year collaborative project between Kent State University (KSU-SLIS) and the University of Maryland (UMD-CIS), which partners with local public libraries, small business development centers, economic development organizations, and community advocacy groups to bring advanced data analytics and business intelligence (DA&BI) services to public libraries in order to support small businesses, entrepreneurs, and community advocates within two recovering communities in Ohio and Maryland.
Long Term Multi-Instruments Land Surface Reflectance Record and Applications
Principal Investigator(s): Sergii Skakun
Funders: NASA - Goddard Space Flight Center Other Non-Federal
Research Areas: Future of Work Machine Learning, AI, Computational Linguistics, and Information Retrieval Smart Cities and Connected Communities
The long-term data record (LTDR) from the Advanced Very High-Resolution Radiometer (AVHRR) provides daily surface reflectance with global coverage from the 1980s to present day, making it a unique source of information for the study of land surface properties and their long-term dynamics. Surface reflectance is a critical input for the generation of products such as vegetation indices, albedo, and land cover. Therefore, it is of utmost importance to quantify its uncertainties to better understand how they might propagate into downstream products.
Principal Investigator(s): Sergii Skakun
Funders: NASA - Goddard Space Flight Center Other Non-Federal
Research Areas: Future of Work Machine Learning, AI, Computational Linguistics, and Information Retrieval Smart Cities and Connected Communities
The long-term data record (LTDR) from the Advanced Very High-Resolution Radiometer (AVHRR) provides daily surface reflectance with global coverage from the 1980s to present day, making it a unique source of information for the study of land surface properties and their long-term dynamics. Surface reflectance is a critical input for the generation of products such as vegetation indices, albedo, and land cover. Therefore, it is of utmost importance to quantify its uncertainties to better understand how they might propagate into downstream products.
M3I – Maps, Models, and Metrics for Influence Efforts by State/Non-State Actors
Principal Investigator(s): Cody Buntain
Funders: DOD-DARPA-Defense Advanced Research Projects Agency Other Non-Federal
Principal Investigator(s): Cody Buntain
Funders: DOD-DARPA-Defense Advanced Research Projects Agency Other Non-Federal
Mapping Inequality — Redlining in New Deal America
Principal Investigator(s): Richard Marciano
Research Areas: Archival Science
Providing online access to the totality of the maps and neighborhood descriptions for the national redlining collection.
Principal Investigator(s): Richard Marciano
Research Areas: Archival Science
Providing online access to the totality of the maps and neighborhood descriptions for the national redlining collection.
Maryland Sports Data Analytics Camps for Youth
Principal Investigator(s): Tamara Clegg
Funders: 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
Funders: 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.