Ten principles for machine-actionable data management plans.
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Data management plans (DMPs) are documents accompanying research proposals and project outputs. DMPs are created as free-form text and describe the data and tools employed in scientific investigations. They are often seen as an administrative exercise and not as an integral part of research practice. There is now widespread recognition that the DMP can have more thematic, machineactionable richness with added value for all stakeholders: researchers, funders, repository managers, research administrators, data librarians, and others. The research community is moving toward a shared goal of making DMPs machine-actionable to improve the experience for all involved by exchanging information across research tools and systems and embedding DMPs in existing workflows. This will enable parts of the DMP to be automatically generated and shared, thus reducing administrative burdens and improving the quality of information within a DMP. This paper presents 10 principles to put machine-.....
JournalPLOS Computational Biology
Issue3, Article e1006750
Sustainable Development Goals (SDG)14.a
Essential Ocean Variables (EOV)N/A
DOI Originalhttps://doi.org/10.1371/journal. pcbi.1006750
CitationMiksa, T., Simms, S., Mietchen, D. and Jones, S. (2019) Ten principles for machine-actionable data management plans. PLoS Computational Biology, 5(3): e1006750, 15pp. DOI: https://doi.org/10.1371/journal. pcbi.1006750
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