Research Projects
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.
Crowdsourced Data: Accuracy, Accessibility, Authority (CDAAA)
Principal Investigator(s): Victoria Van Hyning
Funders: Institute of Museum and Library Services
Research Areas: Accessibility and Inclusive Design Digital Humanities Information Justice, Human Rights, and Technology Ethics Library and Information Science Social Networks, Online Communities, and Social Media
CDAAA explores the sociotechnical barriers libraries, archives, and museums face in integrating crowdsourced transcriptions to discovery systems. Using data from surveys, semi-structured interviews, data integration demonstrations, and user testing with people who use screen readers, we will produce individualized LAM Partner Reports, a summative white paper, and open-access journal articles.
Principal Investigator(s): Victoria Van Hyning
Funders: Institute of Museum and Library Services
Research Areas: Accessibility and Inclusive Design Digital Humanities Information Justice, Human Rights, and Technology Ethics Library and Information Science Social Networks, Online Communities, and Social Media
CDAAA explores the sociotechnical barriers libraries, archives, and museums face in integrating crowdsourced transcriptions to discovery systems. Using data from surveys, semi-structured interviews, data integration demonstrations, and user testing with people who use screen readers, we will produce individualized LAM Partner Reports, a summative white paper, and open-access journal articles.
Designing a Computer Science Pre-service Teacher Methods Course for Maryland
Principal Investigator(s): David Weintrop
Funders: University System of Maryland Other
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval Youth Experience, Learning, and Digital Practices
Principal Investigator(s): David Weintrop
Funders: University System of Maryland Other
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval Youth Experience, Learning, and Digital Practices
Digital Curation Fellows Program at the National Agricultural Library 2021-2026
Principal Investigator(s): Katrina Fenlon
Funders: USDA Agricultural Research Service
Research Areas: 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
Funders: USDA Agricultural Research Service
Research Areas: 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.
FAI: Advancing Deep Learning Towards Spatial Fairness
Principal Investigator(s): Sergii Skakun
Funders: University of Pittsburgh National Science Foundation
Research Areas: Data Science, Analytics, and Visualization Machine Learning, AI, Computational Linguistics, and Information Retrieval
The project aims to address spatial biases in AI, ensuring spatial fairness in real-world applications like agriculture and disaster management. Traditional machine learning struggles with spatial fairness due to data variations. The project proposes new statistical formulations, network architectures, fairness-driven adversarial learning, and a knowledge-enhanced approach for improved spatial dataset analysis. The results will integrate into geospatial software.fference between habits and behaviors ef
Principal Investigator(s): Sergii Skakun
Funders: University of Pittsburgh National Science Foundation
Research Areas: Data Science, Analytics, and Visualization Machine Learning, AI, Computational Linguistics, and Information Retrieval
The project aims to address spatial biases in AI, ensuring spatial fairness in real-world applications like agriculture and disaster management. Traditional machine learning struggles with spatial fairness due to data variations. The project proposes new statistical formulations, network architectures, fairness-driven adversarial learning, and a knowledge-enhanced approach for improved spatial dataset analysis. The results will integrate into geospatial software.fference between habits and behaviors ef
Future of Interface and Accessibility Workshop
Principal Investigator(s): Gregg Vanderheiden
Funders: National Science Foundation
Research Areas: Accessibility and Inclusive Design
This project is focused on looking at the past and future of interface and accessibility including the development of a 20 year R&D agenda
Principal Investigator(s): Gregg Vanderheiden
Funders: National Science Foundation
Research Areas: Accessibility and Inclusive Design
This project is focused on looking at the past and future of interface and accessibility including the development of a 20 year R&D agenda
III: Small: Bringing Transparency and Interpretability to Bias Mitigation Approaches in Place-based Mobility-centric Prediction Models for Decision
Principal Investigator(s): Vanessa Frias-Martinez
Funders: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization Health Informatics Information Justice, Human Rights, and Technology Ethics Machine Learning, AI, Computational Linguistics, and Information Retrieval
The project focuses on improving the fairness of place-based mobility-centric (PBMC) prediction models, particularly in high-stakes scenarios like public health and safety. By addressing biases in COVID-19 mobility and case data, it aims to make predictions more accurate and equitable. The research introduces novel bias-mitigation and interpretability methods across three technical thrusts, promoting transparency in PBMC models.
Principal Investigator(s): Vanessa Frias-Martinez
Funders: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization Health Informatics Information Justice, Human Rights, and Technology Ethics Machine Learning, AI, Computational Linguistics, and Information Retrieval
The project focuses on improving the fairness of place-based mobility-centric (PBMC) prediction models, particularly in high-stakes scenarios like public health and safety. By addressing biases in COVID-19 mobility and case data, it aims to make predictions more accurate and equitable. The research introduces novel bias-mitigation and interpretability methods across three technical thrusts, promoting transparency in PBMC models.
Inclusive ICT Rehabilitation Engineering Research Center (TRACE RERC)
Principal Investigator(s): J. Bern Jordan Amanda Lazar Hernisa Kacorri
Funders: National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR) Other
Research Areas: Accessibility and Inclusive Design Human-Computer Interaction
Principal Investigator(s): J. Bern Jordan Amanda Lazar Hernisa Kacorri
Funders: National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR) Other
Research Areas: Accessibility and Inclusive Design Human-Computer Interaction
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
Inverting Colonial Archival Structures: Increasing Discovery and Access for Indigenous Communities through SNAC (Indigenize SNAC) aims to test discovery and access of archival records for indigenous communities through the web platform Social Networks for Archival Contexts (SNAC). The project is funded by the IMLS Laura Bush 21st Century Librarian program.
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
Inverting Colonial Archival Structures: Increasing Discovery and Access for Indigenous Communities through SNAC (Indigenize SNAC) aims to test discovery and access of archival records for indigenous communities through the web platform Social Networks for Archival Contexts (SNAC). The project is funded by the IMLS Laura Bush 21st Century Librarian program.
Investigating the Information Practices of COVID Long-Haulers
Principal Investigator(s): Beth St. Jean Twanna Hodge Jane Behre J. Nicole Miller
Funders: UMD Impact Award - Pandemic Readiness Initiative: https://research.umd.edu/pri Other
Research Areas: Health Informatics Information Justice, Human Rights, and Technology Ethics Library and Information Science
This project investigates the information needs, practices, and experiences of people who have long COVID ("COVID long-haulers") in order to learn more about their COVID-related information needs, the ways in which they have gone about fulfilling these needs, and their information-related experiences. W
Principal Investigator(s): Beth St. Jean Twanna Hodge Jane Behre J. Nicole Miller
Funders: UMD Impact Award - Pandemic Readiness Initiative: https://research.umd.edu/pri Other
Research Areas: Health Informatics Information Justice, Human Rights, and Technology Ethics Library and Information Science
This project investigates the information needs, practices, and experiences of people who have long COVID ("COVID long-haulers") in order to learn more about their COVID-related information needs, the ways in which they have gone about fulfilling these needs, and their information-related experiences. W
Launching the TALENT Network to Promote the Training of Archival & Library Educators w. iNnovative Technologies
Principal Investigator(s): Richard Marciano
Funders: Institute of Museum and Library Services Other
Research Areas: Archival Science Data Science, Analytics, and Visualization Library and Information Science
The TALENT Network (Training of Archival & Library Educators with iNnovative Technologies) brings together experts from across the United States (including archivists, librarians, Library and Information Science educators, historians, learning scientists, cognitive scientists, computer scientists, and software engineers) in order to create a durable, diverse, and multidisciplinary national community focused on developing digital expertise and leadership skills among archival and library educators.
Principal Investigator(s): Richard Marciano
Funders: Institute of Museum and Library Services Other
Research Areas: Archival Science Data Science, Analytics, and Visualization Library and Information Science
The TALENT Network (Training of Archival & Library Educators with iNnovative Technologies) brings together experts from across the United States (including archivists, librarians, Library and Information Science educators, historians, learning scientists, cognitive scientists, computer scientists, and software engineers) in order to create a durable, diverse, and multidisciplinary national community focused on developing digital expertise and leadership skills among archival and library educators.
Libraries, Integration, and New Americans: Understanding immigrant acculturative stress
Principal Investigator(s): Ana Ndumu
Funders: Institute of Museum and Library Services
Research Areas: Information Justice, Human Rights, and Technology Ethics Library and Information Science
Libraries, Integration, and New Americans,” or L.I.N.A., is a three-year research project directed by Dr. Ana Ndumu that will answer the following questions: What is the role of information in immigrant acculturative stress? How does information-related acculturative
stress impact library access? How can libraries help adult immigrants who are overwhelmed by information? Funding from IMLS under the Laura Bush 21st Century Early Career.
Principal Investigator(s): Ana Ndumu
Funders: Institute of Museum and Library Services
Research Areas: Information Justice, Human Rights, and Technology Ethics Library and Information Science
Libraries, Integration, and New Americans,” or L.I.N.A., is a three-year research project directed by Dr. Ana Ndumu that will answer the following questions: What is the role of information in immigrant acculturative stress? How does information-related acculturative
stress impact library access? How can libraries help adult immigrants who are overwhelmed by information? Funding from IMLS under the Laura Bush 21st Century Early Career.