Amy Pienta
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Research Professor
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About
Dr. Amy Pienta is a Research Professor at the University of Michigan in the United States. Her research focuses on data management, including the legal frameworks for accessing confidential survey data, the practices surrounding restricted data management, and the challenges of sharing qualitative research data. She also investigates the relationships between data properties, curation, and funding in the context of data reuse.
Recent Grants
Grant: Close
Curating and releasing additional RWJF-funded data to expand the Health and Medical Care Archive and continuing to grow the user community, 2022-2024
Open Date: 2022-04-01
Close Date: 2024-03-31
Grant: Close
Expanding access to RWJF Health and Medical Care Archive data and increasing impact by growing the user community engaged with the data, 2021-2022
Open Date: 2021-04-01
Close Date: 2022-03-31
Grant: Close
Increasing the RWJF Health and Medical Care Archive's capacity to collect and disseminate data and to make more data available for reuse, 2020-2021
Open Date: 2020-04-01
Close Date: 2021-03-31
Grant: Close
Developing Evidence-based Data Sharing and Archiving Policies
Open Date: 2019-12-01
Close Date: 2022-11-30
Grant: Close
NATIONAL ADDICTION AND HIV DATA ARCHIVE PROGRAM. APRIL 1, 2019 - MARCH 31, 2024. N01DA-19-5587.
Open Date: 2019-04-01
Close Date: 2023-03-31
Articles (4)
Year:
2023
Year:
2023
Year:
2023
Despite large public investments in facilitating the secondary use of data, there is little information about the specific factors that predict data's reuse. Using data download logs from the Inter‐university Consortium for Political and Social Research (ICPSR), this study examines how data properties, curation decisions, and repository funding models relate to data reuse. We find that datasets deposited by institutions, subject to many curatorial tasks, and whose access and preservation is funded externally, are used more often. Our findings confirm that investments in data collection, curation, and preservation are associated with more data reuse.
Year:
2022
Collaborators (2)
Libby Hemphill
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David A. Bleckley
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