Identifying metadata commonalities across restricted health data sources: A mixed methods study exploring how to improve the discovery of and access to restricted datasets

Metadata is not an inherent characteristic of restricted data, which limits its ability to be found and used. To better understand discoverability and accessibility of restricted data, this study reviewed restricted health data sources to determine how they describe their datasets and access procedures, what descriptive commonalities exist across data sources, and to what extent the commonalities we found can be accommodated within existing metadata schemas. This project includes analysis from three datasets: the first dataset compiles dataset metadata commonalities that were identified from 48 Canadian restricted health data sources. The second dataset compiles request access and access process metadata commonalities extracted from the same 48 data sources. The third dataset maps metadata commonalities of the first dataset to existing metadata standards including DataCite, DDI-Lifecycle and Codebook, DCAT, and DATS. This mapping exercise was completed to determine whether metadata used by restricted data sources aligned with existing standards for research data for improved discovery in the larger FAIR scientific data ecosystem. Read full article (https://doi.org/10.7191/jeslib.907)

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Zenodo (CERN European Organization for Nuclear Research)
Published
2026-01-08
DOI
https://doi.org/10.5281/zenodo.18182378
Primary Topic
Research Data Management Practices
Type
article
Field-Weighted Citation Impact
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article

Identifying metadata commonalities across restricted health data sources: A mixed methods study exploring how to improve the discovery of and access to restricted datasets

Amber Leahey, Victoria Smith, J. Shi, Grant Gibson et al.
Zenodo (CERN European Organization for Nuclear Research)
Research Data Management Practices
article

Identifying metadata commonalities across restricted health data sources: A mixed methods study exploring how to improve the discovery of and access to restricted datasets

Amber Leahey, Victoria Smith, J. Shi, Grant Gibson, Kevin B. Read, Lynn Peterson, Kelly Stathis, Sarah Rutley
article en

Abstract

Metadata is not an inherent characteristic of restricted data, which limits its ability to be found and used. To better understand discoverability and accessibility of restricted data, this study reviewed restricted health data sources to determine how they describe their datasets and access procedures, what descriptive commonalities exist across data sources, and to what extent the commonalities we found can be accommodated within existing metadata schemas. This project includes analysis from three datasets: the first dataset compiles dataset metadata commonalities that were identified from 48 Canadian restricted health data sources. The second dataset compiles request access and access process metadata commonalities extracted from the same 48 data sources. The third dataset maps metadata commonalities of the first dataset to existing metadata standards including DataCite, DDI-Lifecycle and Codebook, DCAT, and DATS. This mapping exercise was completed to determine whether metadata used by restricted data sources aligned with existing standards for research data for improved discovery in the larger FAIR scientific data ecosystem. Read full article (https://doi.org/10.7191/jeslib.907)

Zenodo (CERN European Organization for Nuclear Research)
University of Toronto (CA), University of Saskatchewan (CA), Toronto Dementia Research Alliance (CA), Ontario Council of University Libraries (CA), DataCite (DE), National Research Council Canada (CA), Digital Research Alliance of Canada
Responsible consumption and production
Openalex Percentile: Top 96%
Research Data Management Practices
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