Inactive Research Projects
Heal Us: Reimagining and co-developing curricula for maternal health professionals
Principal Investigator(s): Amelia Gibson
Funders: University of North Carolina at Chapel Hill Other Non-Federal
Research Areas: Data Privacy and Sociotechnical Cybersecurity Health Informatics Information Justice, Human Rights, and Technology Ethics
BELIEVE (which stands For “Building Equitable Linkages With Interprofessional Education Valuing Everyone) is a multi-institutional project focused on developing and testing interprofessional curricular interventions for the purpose of reducing Black maternal mortality and morbidity and improving birth experiences in the United States.
Principal Investigator(s): Amelia Gibson
Funders: University of North Carolina at Chapel Hill Other Non-Federal
Research Areas: Data Privacy and Sociotechnical Cybersecurity Health Informatics Information Justice, Human Rights, and Technology Ethics
BELIEVE (which stands For “Building Equitable Linkages With Interprofessional Education Valuing Everyone) is a multi-institutional project focused on developing and testing interprofessional curricular interventions for the purpose of reducing Black maternal mortality and morbidity and improving birth experiences in the United States.
How COVID-19 is Changing Workplace Surveillance: American Workers’ Experiences & Privacy Expectations When Working From Home
Principal Investigator(s): Jessica Vitak
Funders: SSRC Rapid-Response Research Grants 2020 Other Non-Federal
Research Areas: Future of Work
Investigating American workers' attitudes toward workplace surveillance, including employers' collection of their data for workplace monitoring and efficiency tracking, which has shifted to working-at-home surveillance due to Covid-19.
Principal Investigator(s): Jessica Vitak
Funders: SSRC Rapid-Response Research Grants 2020 Other Non-Federal
Research Areas: Future of Work
Investigating American workers' attitudes toward workplace surveillance, including employers' collection of their data for workplace monitoring and efficiency tracking, which has shifted to working-at-home surveillance due to Covid-19.
Human-Agent Teaming on Intelligence Tasks
Principal Investigator(s): Susannah Paletz
Research Areas: Future of Work
Our goal is to create a platform for running experiments that would simulate an AI intervention into intelligence analysis tasks, specifically involving a human shift handover. Participants would work through materials, including notes and feedback from the “previous” analyst, to solve a fictional intelligence task. This study examines how potential AIs can influence team cognition and decision making.
Principal Investigator(s): Susannah Paletz
Research Areas: Future of Work
Our goal is to create a platform for running experiments that would simulate an AI intervention into intelligence analysis tasks, specifically involving a human shift handover. Participants would work through materials, including notes and feedback from the “previous” analyst, to solve a fictional intelligence task. This study examines how potential AIs can influence team cognition and decision making.
IARPA BETTER: Multilingual Fine-grained Decompositional Analysis
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval
Developing enhanced methods for personalized, multilingual semantic extraction and retrieval from text, in support of IARPA's goal of providing users with a system that quickly and accurately extracts complex semantic information, targeted for a specific user, from text.
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval
Developing enhanced methods for personalized, multilingual semantic extraction and retrieval from text, in support of IARPA's goal of providing users with a system that quickly and accurately extracts complex semantic information, targeted for a specific user, from text.
III: Small: DataWorld: Externalizing Hidden Data Flows for Anywhere Analytics
Funders: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization Information Justice, Human Rights, and Technology Ethics Library and Information Science Machine Learning, AI, Computational Linguistics, and Information Retrieval
Building an augmented-reality DataWorld using hidden troves of data (from social media, the census, public databases, and more) to help professionals, policymakers, and citizens in there every day life---from house hunting by walking through the neighborhood and getting pop-up facts about the area to getting event and safety updates as you walk through a college campus.
Funders: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization Information Justice, Human Rights, and Technology Ethics Library and Information Science Machine Learning, AI, Computational Linguistics, and Information Retrieval
Building an augmented-reality DataWorld using hidden troves of data (from social media, the census, public databases, and more) to help professionals, policymakers, and citizens in there every day life---from house hunting by walking through the neighborhood and getting pop-up facts about the area to getting event and safety updates as you walk through a college campus.
III: Small: Improving Technical Paper Database Search through Math-aware Search Engines
Principal Investigator(s): Douglas W. Oard
Funders: Rochester Institute of Technology Other Non-Federal
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval Library and Information Science
Principal Investigator(s): Douglas W. Oard
Funders: Rochester Institute of Technology Other Non-Federal
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval Library and Information Science
III:Small:Safely Searching Among Sensitive Content
Principal Investigator(s): Douglas W. Oard Katie Shilton
Funders: National Science Foundation
Research Areas: Data Privacy and Sociotechnical Cybersecurity Data Science, Analytics, and Visualization Information Justice, Human Rights, and Technology Ethics Library and Information Science
Today's search engines are designed principally to help people find what they want to see. Paradoxically, the fact that search engines do this well means that there are many collections that can't be searched.
Principal Investigator(s): Douglas W. Oard Katie Shilton
Funders: National Science Foundation
Research Areas: Data Privacy and Sociotechnical Cybersecurity Data Science, Analytics, and Visualization Information Justice, Human Rights, and Technology Ethics Library and Information Science
Today's search engines are designed principally to help people find what they want to see. Paradoxically, the fact that search engines do this well means that there are many collections that can't be searched.
Improving Data Discovery at the National Anthropological Archives: Pilot Study and National Survey
Principal Investigator(s): Diana E. Marsh
Funders: National Science Foundation
Research Areas: Accessibility and Inclusive Design Library and Information Science
Based on a three-year fellowship supported by the National Science Foundation, this research seeks to improve the discovery of anthropological archives for users. Current work includes exploring data reuse based on a national survey undertaken in 2018-2019 with the Association of Tribal Archives, Libraries, and Museums and the American Anthropological Association.
Principal Investigator(s): Diana E. Marsh
Funders: National Science Foundation
Research Areas: Accessibility and Inclusive Design Library and Information Science
Based on a three-year fellowship supported by the National Science Foundation, this research seeks to improve the discovery of anthropological archives for users. Current work includes exploring data reuse based on a national survey undertaken in 2018-2019 with the Association of Tribal Archives, Libraries, and Museums and the American Anthropological Association.
Improving Fedora 4 to Work with Web-Scale Storage and Services
Principal Investigator(s): Richard Marciano
Funders: Institute of Museum and Library Services
Research Areas: Archival Science
The Digital Curation Innovation Center plans to improve the performance and scalability of the Fedora Repository for the Fedora community by researching, developing, and testing software architectures.
Principal Investigator(s): Richard Marciano
Funders: Institute of Museum and Library Services
Research Areas: Archival Science
The Digital Curation Innovation Center plans to improve the performance and scalability of the Fedora Repository for the Fedora community by researching, developing, and testing software architectures.
Inclusive ICT RERC
Principal Investigator(s): Gregg Vanderheiden J. Bern Jordan Hernisa Kacorri Amanda Lazar Jonathan Lazar
Funders: HHS / ACL / National Institute on Disability, Independent Living, and Rehabilitation Research Other Non-Federal
Research Areas: Accessibility and Inclusive Design Data Science, Analytics, and Visualization Human-Computer Interaction Information Justice, Human Rights, and Technology Ethics
Ensuring that existing information and communication technologies (ICT) solutions for people with disabilities are known, effective, findable, more affordable, and available on every computer or digital technology platform; and exploring the emerging next-next-generation interface technologies for which there are no effective accessibility guidelines or standards, and problem-solving in advance of these technologies.
Principal Investigator(s): Gregg Vanderheiden J. Bern Jordan Hernisa Kacorri Amanda Lazar Jonathan Lazar
Funders: HHS / ACL / National Institute on Disability, Independent Living, and Rehabilitation Research Other Non-Federal
Research Areas: Accessibility and Inclusive Design Data Science, Analytics, and Visualization Human-Computer Interaction Information Justice, Human Rights, and Technology Ethics
Ensuring that existing information and communication technologies (ICT) solutions for people with disabilities are known, effective, findable, more affordable, and available on every computer or digital technology platform; and exploring the emerging next-next-generation interface technologies for which there are no effective accessibility guidelines or standards, and problem-solving in advance of these technologies.
INFACT: The Inclusion of Neurodiversity in Foundations and Applications of Computational Thinking
Principal Investigator(s): David Weintrop
Funders: TERC Other Non-Federal
Research Areas: Accessibility and Inclusive Design Machine Learning, AI, Computational Linguistics, and Information Retrieval
Principal Investigator(s): David Weintrop
Funders: TERC Other Non-Federal
Research Areas: Accessibility and Inclusive Design Machine Learning, AI, Computational Linguistics, and Information Retrieval
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