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Data sharing is increasingly an expectation in health research as part of a general move toward more open sciences. In the United States, in particular, the implementation of the 2023 National Institutes of Health Data Management and Sharing Policy has made it clear that qualitative studies are not exempt from this data sharing requirement. Recognizing this trend, the Palliative Care Research Cooperative Group (PCRC) realized the value of creating a de-identified qualitative data repository to complement its existing de-identified quantitative data repository. The PCRC Data Informatics and Statistics Core leadership partnered with the Qualitative Data Repository (QDR) to establish the first serious illness and palliative care qualitative data repository in the U.S. We describe the processes used to develop this repository, called the PCRC-QDR, as well as our outreach and education among the palliative care researcher community, which led to the first ten projects to share the data in the new repository. Specifically, we discuss how we co-designed the PCRC-QDR and created tailored guidelines for depositing and sharing qualitative data depending on the original research context, establishing uniform expectations for key components of relevant documentation, and the use of suitable access controls for sensitive data. We also describe how PCRC was able to leverage its existing community to recruit and guide early depositors and outline lessons learned in evaluating the experience. This work advances the establishment of best practices in qualitative data sharing.
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DataVault: a data storage infrastructure for the Einstein Toolkit
Abstract Data sharing is essential in the numerical simulations research. We introduce a data repository, DataVault, which is designed for data sharing, search and analysis. A comparative study of existing repositories is performed to analyze features that are critical to a data repository. We describe the architecture, workflow, and deployment of DataVault, and provide three use-case scenarios for different communities to facilitate the use and application of DataVault. Potential features are proposed and we outline the future development for these features.
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- Award ID(s):
- 2004879
- PAR ID:
- 10320826
- Date Published:
- Journal Name:
- Classical and Quantum Gravity
- Volume:
- 38
- Issue:
- 13
- ISSN:
- 0264-9381
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1088/1361-6382/abf9b5
