• Output Type: Working Group Supporting Output
  • Output Status: Endorsed
  • Review Period End: 2020-07-17
  • Abstract

    Persistent Identification of Instruments WG

    Group co-chairs: Louise Darroch, Markus Stocker, Rolf Krahl, Ted Habermann

    Supporting Output Title: Persistent Identification of Instruments

    Authors: Markus Stocker, Louise Darroch, Rolf Krahl, Ted Habermann, Anusiriya Devaraju, Ulrich Schwardmann, Claudio D’onofrio, Ingemar Häggström

    Impact: Provides two tested approaches for persistent identification of instruments.

    Supporting Output package DOI: 10.5334/dsj-2020-018

    Citation: Stocker, M., Darroch, L., Krahl, R., Habermann, T., Devaraju, A., Schwardmann, U., D’Onofrio, C. and Häggström, I., 2020. Persistent Identification of Instruments. Data Science Journal, 19(1), p.18. DOI: http://doi.org/10.5334/dsj-2020-018

    Abstract

    Instruments play an essential role in creating research data.  Given the importance of instruments and associated metadata to the asssessment of data quality and data reuse, globally unique, persistnet 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.

  • Group Technology focus: Data (Output) Management Planning
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