Application Profile for Machine- Actionable Data Management Plans.

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Date
2021
Author
Miksa, T.
Walk, Paul
Neish, Peter
Oblasser, Simon
HOLLAND, MURRAY
Renner, Tom
Jacquemot-Perbal, M-C.
Cardoso, Joao
Kvamme, Trond
Praetzellis, Maria
Suchánek, Marek
Hooft, Rob
Faure, Benjamin
Moa, Hanne
Hasan, Adil
Jones, Sarah
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Abstract
This paper presents the application profile for machine-actionable data management plans that allows information from traditional data management plans to be expressed in a machine-actionable way. We describe the methodology and research conducted to define the application profile. We also discuss design decisions made during its development and present systems which have adopted it. The application profile was developed in an open and consensus-driven manner within the DMP Common Standards Working Group of the Research Data Alliance and is its official recommendation.....
Resource URL
Publisher: https://datascience.codata.org/article/10.5334/dsj-2021-032/
Journal
Data Science Journal
Volume
20
Issue
1
Page Range
pp.32-49
Document Language
en
Essential Ocean Variables (EOV)
N/A
DOI Original
https:// doi.org/10.5334/dsj-2021-032
Citation
Miksa, T., Walk, P., Neish, P., Oblasser, S., Murray, H., Renner, T., Jacquemot-Perbal, M-C., Cardoso, J., Kvamme, T., Praetzellis, M., Suchánek, M., Hooft, R., Faure, B., Moa, H., Hasan, A. and Jones, S. (2021) Application Profile for Machine- Actionable Data Management Plans. Data Science Journal, 20: pp. 32-49. DOI: https:// doi.org/10.5334/dsj-2021-032
URI
https://repository.oceanbestpractices.org/handle/11329/1784
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Attribution 4.0 International
Except where otherwise noted, this item's license is described as Attribution 4.0 International