Persistent identification of instruments

Stocker, Markus; Darroch, Louise; Krahl, Rolf; Habermann, Ted; Devaraju, Anusuriya; Schwardmann, Ulrich; D’Onofrio, Claudio; Häggström, Ingemar. 2020 Persistent identification of instruments. Data Science Journal, 19. 18, pp. https://doi.org/10.5334/dsj-2020-018

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Official URL: http://dx.doi.org/10.5334/dsj-2020-018

Abstract/Summary

Instruments play an essential role in creating research data. Given the importance of instruments and associated metadata to the assessment of data quality and data reuse, globally unique, persistent and resolvable identification of instruments is crucial. The Research Data Alliance Working Group Persistent Identification of Instruments (PIDINST) developed a community-driven solution for persistent identification of instruments which we present and discuss in this paper. Based on an analysis of 10 use cases, PIDINST developed a metadata schema and prototyped schema implementation with DataCite and ePIC as representative persistent identifier infrastructures and with HZB (Helmholtz-Zentrum Berlin für Materialien und Energie) and BODC (British Oceanographic Data Centre) as representative institutional instrument providers. These implementations demonstrate the viability of the proposed solution in practice. Moving forward, PIDINST will further catalyse adoption and consolidate the schema by addressing new stakeholder requirements.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.5334/dsj-2020-018
ISSN:	1683-1470
Date made live:	11 Jun 2020 14:54 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/527952

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.5334/dsj-2020-018

ISSN:

1683-1470

Date made live:

11 Jun 2020 14:54 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/527952