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Persistent identification of instruments

2020, Stocker, M., Darroch, L., Krahl, R., Habermann, T., Devaraju, A., Schwardmann, U., D’onofrio, C., Häggström, I.

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.

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PID Network Deutschland: Netzwerk für die Förderung von persistenten Identifikatoren in Wissenschaft und Kultur

2023, Bertelmann, Roland, Buys, Matthew, Kett, Jürgen, Pampel, Heinz, Pieper, Dirk, Scholze, Frank, Sens, Irina, Burger, Felix, Dreyer, Britta, Glagla-Dietz, Stephanie, Hagemann- Wilholt, Stephanie, Hartmann, Sarah, Schrader, Antonia C., Schirrwagen, Jochen, Summann, Friedrich, Vierkant, Paul

[No abstract available]

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FAIRly connected - Ressourcen vernetzen

2022, Burger, Felix

Damit eine veröffentlichte Ressource die FAIR-Prinzipien erfüllen kann, bedarf es qualitativ hochwertiger Metadaten, welche nicht nur die Ressource selbst, sondern auch mit ihr in Verbindung stehende Objekte beschreiben. Diese Verknüpfungen werden vom Poster anhand des DataCite-Metadatenschemas dargestellt. Der Fokus liegt hierbei auf dem Property "relatedIdentifier". Mittels ausgewählter Beispiele werden die FAIR-Kategorien illustriert und Anregungen geliefert, sowie exemplarische Herausforderungen und Fragestellungen bei der DOI-Metadatenvergabe vorgestellt.

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DOIs für Blog-Beiträge: Herausforderungen und Best Practice

2022-11-28, Taller, Nelli

Folien für den virtuellen Workshop "DOIs für Blog-Beiträge: Herausforderungen und Best Practice".

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A short guide to increase FAIRness of atmospheric model data

2020, Ganske, Anette, Heydebreck, Daniel, Höck, Daniel, Kraft, Angelina, Quaas, Johannes, Kaiser, Amandine

The generation, processing and analysis of atmospheric model data are expensive, as atmospheric model runs are often computationally intensive and the costs of ‘fast’ disk space are rising. Moreover, atmospheric models are mostly developed by groups of scientists over many years and therefore only few appropriate models exist for specific analyses, e.g. for urban climate. Hence, atmospheric model data should be made available for reuse by scientists, the public sector, companies and other stakeholders. Thereby, this leads to an increasing need for swift, user-friendly adaptation of standards.The FAIR data principles (Findable, Accessible, Interoperable, Reusable) were established to foster the reuse of data. Research data become findable and accessible if they are published in public repositories with general metadata and Persistent Identifiers (PIDs), e.g. DataCite DOIs. The use of PIDs should ensure that describing metadata is persistently available. Nevertheless, PIDs and basic metadata do not guarantee that the data are indeed interoperable and reusable without project-specific knowledge. Additionally, the lack of standardised machine-readable metadata reduces the FAIRness of data. Unfortunately, there are no common standards for non-climate models, e.g. for mesoscale models, available. This paper proposes a concept to improve the FAIRness of archived atmospheric model data. This concept was developed within the AtMoDat project (Atmospheric Model Data). The approach consists of several aspects, each of which is easy to implement: requirements for rich metadata with controlled vocabulary, the landing pages, file formats (netCDF) and the structure within the files. The landing pages are a core element of this concept as they should be human- and machine readable, hold discipline-specific metadata and present metadata on simulation and variable level. This guide is meant to help data producers and curators to prepare data for publication. Furthermore, this guide provides information for the choice of keywords, which supports data reusers in their search for data with search engines. © 2020 The authors

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TIB DOI Konsortium: Was ändert sich und wie geht es weiter?

2020-11-13, Taller, Nelli, Dreyer, Britta, Burger, Felix

Folien für den virtuellen Workshop "TIB DOI Konsortium: Was ändert sich und wie geht es weiter?".

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Retrodigitalisierung in der TIB

2023-05-02, Wehrhahn, Dawn, Kehm, Nicole

Folien zum Thema Retrodigitalisierung für den virtuellen Workshop "Frühlings TIB DOI Konsortium Workshop - Retrodigitalisierung und Langzeitarchivierung".

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Persistent Identification Of Instruments

2020, Stocker, Markus, Darroch, Louise, Krahl, Rolf, Habermann, Ted, Devaraju, Anusuriya, Schwardmann, Ulrich, D'Onofrio, Claudio, Häggström, Ingemar

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.

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Herbst TIB DOI Konsortium online Workshops - Metadaten Best Practice

2021-11-09, Taller, Nelli, Dreyer, Britta, Burger, Felix, Hagemann-Wilholt, Stephanie

Folien für den virtuellen Workshop "Herbst TIB DOI Konsortium online Workshops - Metadaten Best Practice".

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Herbst TIB DOI Konsortium online Workshop - IGSN, ConfIDent und Metadatenschemata 4.5 und 5.0

2022-11-09, Taller, Nelli, Burger, Felix, Franken, Julian

Folien für den virtuellen Workshop "Herbst TIB DOI Konsortium online Workshop - IGSN, ConfIDent und Metadatenschemata 4.5 und 5.0".