DMPFrame: A Conceptual Metadata Framework for Data Management Plans
Research Data Management (RDM) is a complex process and to ensure good RDM practice, one of the ways is to associate or create Data Management Plans (DMPs) with every research project. Interestingly this opens up other challenges such as finding the corresponding DMP for a research dataset. It is so...
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| Published in: | Journal of library metadata 2023-10, Vol.23 (3-4), p.121-160 |
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| Main Authors: | , |
| Format: | Article |
| Language: | eng |
| Subjects: | |
| Online Access: | Get full text |
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| Summary: | Research Data Management (RDM) is a complex process and to ensure good RDM practice, one of the ways is to associate or create Data Management Plans (DMPs) with every research project. Interestingly this opens up other challenges such as finding the corresponding DMP for a research dataset. It is sometimes difficult or impossible to find a particular DMP associated with a dataset, which undermines the actual value of DMPs. This is the result of poor metadata management of DMPs throughout their creation using a DMP tool to their archiving. Implementing adequate metadata management for the description and organization of DMPs might solve this issue. We have examined 12 open-source DMP tools, in particular, to evaluate the metadata adopted by these tools. The current study spots and highlights the gaps in the DMP metadata management in DMP tools and suggests DMPFrame as a conceptual framework addressing such gaps to improve the existing tools' DMP metadata management practices. Based on the examined DMP tool's metadata elements analysis and mapping, DMPFrame manages DMP metadata under 6 categories, namely, contributors, project, funding, organization, DMP, and output. The current study also suggests a systematic workflow that DMP tools could incorporate for metadata creation for DMPs. |
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| ISSN: | 1938-6389 1937-5034 |