Difference between revisions of "Journal:Persistent identification of instruments"

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==Introduction==
==Introduction==
Between March 2018 and October 2019, the Research Data Alliance (RDA) Working Group (WG) Persistent Identification of Instruments (PIDINST) explored a community-driven solution for globally unambiguous and [[wikipedia:Persistent identifier|persistent identification]] of operational scientific measuring instruments. A "measuring instrument" is understood to be a “device used for making measurements, alone or in conjunction with one or more supplementary devices,” as defined by the Joint Committee for Guides in Metrology (JCGM).<ref name="JCGM_Measuring12">{{cite book |url=https://www.bipm.org/en/publications/guides/#vim |chapter=3.1 measuring instrument |title=International vocabulary of metrology – Basic and general concepts and associated terms (VIM) |author=Joint Committee for Guides in Metrology |publisher=Joint Committee for Guides in Metrology |page=34 |edition=3rd |year=2012}}</ref> Hence, PIDINST chose to address the problem of persistently identifying the devices themselves (i.e., each unique device), the real-world assets with instantaneous capabilities and configurations, rather than the identification of material instrument designs (i.e., models).
Instruments are employed in numerous and diverse scientific disciplines. Instruments can be static (e.g., weather station, [[laboratory]] instrument) or mobile when mounted on moving platforms (e.g., remotely operated underwater vehicles, drones). They may be used in observation or experimentation research activities. They may be owned and operated by individual researchers, research groups, national, international, or global research infrastructures or other types of institutions. For instance, at the time of writing, the [https://www.icos-cp.eu/ Integrated Carbon Observation System] (ICOS) operates approximately 3,000 instruments at over 130 stations in 12 European countries. Astronomy is well known for their intense use of telescopes. Those working in the [[life sciences]] employ an array of instrument types, ranging from microscopes to [[Sequencing|sequencers]]. The engineering sciences, too, make heavy use of instruments.
Persistent identifiers (PIDs) have a long tradition for the globally unique identification of entities relevant to or involved in research. They were developed “to address challenges arising from the distributed and disorganised nature of the internet, which often resulted in URLs to internet endpoints becoming invalid,” (Klump and Huber, 2017) making it difficult to maintain a persistent record of science. Examples for well established persistent identifiers include:
* the [[wikipedia:Digital object identifier|digital object identifier]] (DOI), used to identify literature, data files, and other objects<ref name="PaskinDigital09">{{cite book |chapter=Digital Object Identifier (DOI®) System |title=Encyclopedia of Library and Information Sciences |author=Paskin, N. |editor=Bates, M.J.; Maack, M.N. |publisher=Taylor & Francis Group |edition=3rd |pages=1586–92 |year=2009 |doi=10.1081/e-elis3-120044418}}</ref>;
* the [[wikipedia:ORCID|Open Researcher and Contributor ID]] (ORCID), a persistent identifier for identifying researchers<ref name="HaakORCID12">{{cite journal |title=ORCID: a system to uniquely identify researchers |journal=Learned Publishing |author=Haak, L.L.; Fenner, M.; Paglione, L. et al. |volume=25 |issue=4 |pages=259–64 |year=2012 |doi=10.1087/20120404}}</ref>;
* the [[wikipedia:International Geo Sample Number|International Geo Sample Number]] (IGSN), a persistent identifier for physical [[Sample (material)|samples]] and sample collections<ref name="DevarajuRepre16">{{cite journal |title=Representing and publishing physical sample descriptions |journal=Computers & Geosciences |author=Devaraju, A.; Klump, J.; Cox, S.J.D. et al. |volume=96 |pages=1–10 |year=2016 |doi=10.1016/j.cageo.2016.07.018}}</ref>;
* the [https://ror.org/ Research Organization Registry] (ROR), a persistent identifier for organizations; and
* the [[wikipedia:SciCrunch#Research Resource Identifier|Research Resource Identifier]] (RRID), an identifier for physical resources, such as mice and antibodies, in the life sciences.<ref name="BandrowskiTheRes15">{{cite journal |title=The Resource Identification Initiative: A cultural shift in publishing (Version 2, Peer review 2 approved) |journal=F1000Research |author=Bandrowkski, A.; Brush, M.; Grethe, J.S. et al. |volume=4 |at=134 |year=2015 |doi=10.12688/f1000research.6555.2}}</ref>




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==Notes==
==Notes==
This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added.
This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added. The original article lists references in alphabetical order; however, this version lists them in order of appearance, by design. All footnotes—which are simply URLs—from the original article were turned into either external links or full citations for this version.


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Revision as of 21:58, 15 September 2020

Full article title Persistent identification of instruments
Journal Data Science Journal
Author(s) Stocker, Markus; Darroch, Louise; Krahl, Rolf; Habermann, Ted; Devaraju, Anusuriya; Schwardmann, Ulrich;
D'Onofrio, Claudio; Häggström, Ingemar
Author affiliation(s) TIB Leibniz Information Centre for Science and Technology, University of Bremen, British Oceanographic Data Centre,
Helmholtz-Zentrum Berlin für Materialien und Energie, Metadata Game Changers, Gesellschaft für wissenschaftliche
Datenverarbeitung Göttingen, Lund University, EISCAT Scientific Association
Primary contact Email: markus dot stocker at tib dot eu
Year published 2020
Volume and issue 19(1)
Article # 18
DOI 10.5334/dsj-2020-018
ISSN 1683-1470
Distribution license Creative Commons Attribution 4.0 International
Website https://datascience.codata.org/articles/10.5334/dsj-2020-018/
Download https://datascience.codata.org/articles/10.5334/dsj-2020-018/galley/962/download/ (PDF)

Abstract

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 the 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 catalyze adoption and consolidate the schema by addressing new stakeholder requirements.

Keywords: persistent identification, instruments, metadata, DOI, handle

Introduction

Between March 2018 and October 2019, the Research Data Alliance (RDA) Working Group (WG) Persistent Identification of Instruments (PIDINST) explored a community-driven solution for globally unambiguous and persistent identification of operational scientific measuring instruments. A "measuring instrument" is understood to be a “device used for making measurements, alone or in conjunction with one or more supplementary devices,” as defined by the Joint Committee for Guides in Metrology (JCGM).[1] Hence, PIDINST chose to address the problem of persistently identifying the devices themselves (i.e., each unique device), the real-world assets with instantaneous capabilities and configurations, rather than the identification of material instrument designs (i.e., models).

Instruments are employed in numerous and diverse scientific disciplines. Instruments can be static (e.g., weather station, laboratory instrument) or mobile when mounted on moving platforms (e.g., remotely operated underwater vehicles, drones). They may be used in observation or experimentation research activities. They may be owned and operated by individual researchers, research groups, national, international, or global research infrastructures or other types of institutions. For instance, at the time of writing, the Integrated Carbon Observation System (ICOS) operates approximately 3,000 instruments at over 130 stations in 12 European countries. Astronomy is well known for their intense use of telescopes. Those working in the life sciences employ an array of instrument types, ranging from microscopes to sequencers. The engineering sciences, too, make heavy use of instruments.

Persistent identifiers (PIDs) have a long tradition for the globally unique identification of entities relevant to or involved in research. They were developed “to address challenges arising from the distributed and disorganised nature of the internet, which often resulted in URLs to internet endpoints becoming invalid,” (Klump and Huber, 2017) making it difficult to maintain a persistent record of science. Examples for well established persistent identifiers include:


References

  1. Joint Committee for Guides in Metrology (2012). "3.1 measuring instrument". International vocabulary of metrology – Basic and general concepts and associated terms (VIM) (3rd ed.). Joint Committee for Guides in Metrology. p. 34. https://www.bipm.org/en/publications/guides/#vim. 
  2. Paskin, N. (2009). "Digital Object Identifier (DOI®) System". In Bates, M.J.; Maack, M.N.. Encyclopedia of Library and Information Sciences (3rd ed.). Taylor & Francis Group. pp. 1586–92. doi:10.1081/e-elis3-120044418. 
  3. Haak, L.L.; Fenner, M.; Paglione, L. et al. (2012). "ORCID: a system to uniquely identify researchers". Learned Publishing 25 (4): 259–64. doi:10.1087/20120404. 
  4. Devaraju, A.; Klump, J.; Cox, S.J.D. et al. (2016). "Representing and publishing physical sample descriptions". Computers & Geosciences 96: 1–10. doi:10.1016/j.cageo.2016.07.018. 
  5. Bandrowkski, A.; Brush, M.; Grethe, J.S. et al. (2015). "The Resource Identification Initiative: A cultural shift in publishing (Version 2, Peer review 2 approved)". F1000Research 4: 134. doi:10.12688/f1000research.6555.2. 

Notes

This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added. The original article lists references in alphabetical order; however, this version lists them in order of appearance, by design. All footnotes—which are simply URLs—from the original article were turned into either external links or full citations for this version.