Research Projects
Collaborative Research: SaTC: CORE: Medium: Supporting Privacy Negotiation Among Multiple Stakeholders in Smart Environments
Principal Investigator(s): Jessica Vitak
Funders: National Science Foundation
Research Areas: Data Privacy and Sociotechnical Cybersecurity
Internet-of-Things devices are increasingly used in shared spaces (e.g., homes, apartments, schools, hospitals, workplaces), and different stakeholders in these environments have unique privacy needs and expectations. This project investigates privacy negotiation behaviors in smart environments by designing, developing, and deploying an interactive system to collect people’s real-world privacy negotiation behaviors.
Principal Investigator(s): Jessica Vitak
Funders: National Science Foundation
Research Areas: Data Privacy and Sociotechnical Cybersecurity
Internet-of-Things devices are increasingly used in shared spaces (e.g., homes, apartments, schools, hospitals, workplaces), and different stakeholders in these environments have unique privacy needs and expectations. This project investigates privacy negotiation behaviors in smart environments by designing, developing, and deploying an interactive system to collect people’s real-world privacy negotiation behaviors.
Collaborative Research: Using Artificial Intelligence To Improve Administration of the Freedom of Information Act (FOIA)
Principal Investigator(s): Jason R. Baron Douglas W. Oard
Funders: Unfunded Other Non-Federal
Research Areas: Archival Science Machine Learning, AI, Computational Linguistics, and Information Retrieval
Memorandum of Understanding with MITRE Corporation to research the application of various forms of artificial intelligence (AI) including machine learning (ML) methods to aid in the redaction of documents corresponding to one or more FOIA exemptions.
Principal Investigator(s): Jason R. Baron Douglas W. Oard
Funders: Unfunded Other Non-Federal
Research Areas: Archival Science Machine Learning, AI, Computational Linguistics, and Information Retrieval
Memorandum of Understanding with MITRE Corporation to research the application of various forms of artificial intelligence (AI) including machine learning (ML) methods to aid in the redaction of documents corresponding to one or more FOIA exemptions.
Computational Thinking to Unlock the Japanese American WWII Camp Experience
Principal Investigator(s): Richard Marciano
Funders: Unfunded
Research Areas: Archival Science Machine Learning, AI, Computational Linguistics, and Information Retrieval
Exploring the legacy of WWII Japanese American Incarceration through computational archival science approaches.
Principal Investigator(s): Richard Marciano
Funders: Unfunded
Research Areas: Archival Science Machine Learning, AI, Computational Linguistics, and Information Retrieval
Exploring the legacy of WWII Japanese American Incarceration through computational archival science approaches.
Computational Treatments to re-member the Legacy of Slavery (CT-LoS)
Principal Investigator(s): Richard Marciano
Funders: Unfunded
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
Funders: Unfunded
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.
Computer and Information Science and Engineering Graduate Fellowships (CSGrad4US) – Micah Morgan
Principal Investigator(s): Sheena Erete
Funders: Computing Research Association Other Non-Federal
Principal Investigator(s): Sheena Erete
Funders: Computing Research Association Other Non-Federal
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.
DASS: Learning Code(s): Community-Centered Design of Automated Content Moderation
Principal Investigator(s): Katie Shilton
Funders: National Science Foundation
Research Areas: Accessibility and Inclusive Design Machine Learning, AI, Computational Linguistics, and Information Retrieval Social Networks, Online Communities, and Social Media
Principal Investigator(s): Katie Shilton
Funders: National Science Foundation
Research Areas: Accessibility and Inclusive Design Machine Learning, AI, Computational Linguistics, and Information Retrieval Social Networks, Online Communities, and Social Media
Designing a Computer Science Pre-service Teacher Methods Course for Maryland
Principal Investigator(s): David Weintrop
Funders: State of MD
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval Youth Experience, Learning, and Digital Practices
Principal Investigator(s): David Weintrop
Funders: State of MD
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval Youth Experience, Learning, and Digital Practices
Designing AI-powered DIY Communication Tools with AAC users
Principal Investigator(s): Stephanie Valencia²
Funders: Corporation
Research Areas: Accessibility and Inclusive Design Human-Computer Interaction Machine Learning, AI, Computational Linguistics, and Information Retrieval
Principal Investigator(s): Stephanie Valencia²
Funders: Corporation
Research Areas: Accessibility and Inclusive Design Human-Computer Interaction Machine Learning, AI, Computational Linguistics, and Information Retrieval
Detecting and Mapping War-induced Damage to Agricultural Fields in Ukraine using Multi-Modal Remote Sensing Data
Principal Investigator(s): Sergii Skakun
Funders: NASA - Proposal Only Other Federal
Research Areas: Data Science, Analytics, and Visualization Human-Computer Interaction Machine Learning, AI, Computational Linguistics, and Information Retrieval Smart Cities and Connected Communities Social Networks, Online Communities, and Social Media
Principal Investigator(s): Sergii Skakun
Funders: NASA - Proposal Only Other Federal
Research Areas: Data Science, Analytics, and Visualization Human-Computer Interaction Machine Learning, AI, Computational Linguistics, and Information Retrieval Smart Cities and Connected Communities Social Networks, Online Communities, and Social Media
Digital Curation Fellows Program at the National Agricultural Library 2021-2026
Principal Investigator(s): Katrina Fenlon
Funders: US Department of Agriculture
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: US Department of Agriculture
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.
Ethical VR/AR/XR Research Design with Youth and Families
Principal Investigator(s): beth bonsignore Tamara Clegg
Funders: University of Iowa Other Non-Federal
Principal Investigator(s): beth bonsignore Tamara Clegg
Funders: University of Iowa Other Non-Federal