A short guide to increase FAIRness of atmospheric model data

dc.bibliographicCitation.firstPage483eng
dc.bibliographicCitation.issue6eng
dc.bibliographicCitation.journalTitleMeteorologische Zeitschrift = Contributions to atmospheric scienceseng
dc.bibliographicCitation.lastPage491eng
dc.bibliographicCitation.volume29eng
dc.contributor.authorGanske, Anette
dc.contributor.authorHeydebreck, Daniel
dc.contributor.authorHöck, Daniel
dc.contributor.authorKraft, Angelina
dc.contributor.authorQuaas, Johannes
dc.contributor.authorKaiser, Amandine
dc.date.accessioned2021-11-24T06:55:33Z
dc.date.available2021-11-24T06:55:33Z
dc.date.issued2020
dc.description.abstractThe 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 authorseng
dc.description.versionpublishedVersioneng
dc.identifier.urihttps://oa.tib.eu/renate/handle/123456789/7420
dc.identifier.urihttps://doi.org/10.34657/6467
dc.language.isoengeng
dc.publisherStuttgart : E. Schweizerbart Science Publisherseng
dc.relation.doihttps://doi.org/10.1127/METZ/2020/1042
dc.relation.essn1610-1227
dc.rights.licenseCC BY-NC 4.0 Unportedeng
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/eng
dc.subject.ddc550eng
dc.subject.otherAtMoDateng
dc.subject.otherControlled Vocabularyeng
dc.subject.otherDOIeng
dc.subject.otherFAIReng
dc.subject.otherMetadataeng
dc.titleA short guide to increase FAIRness of atmospheric model dataeng
dc.typeArticleeng
dc.typeTexteng
tib.accessRightsopenAccesseng
wgl.contributorTIBeng
wgl.subjectGeowissenschafteneng
wgl.typeZeitschriftenartikeleng
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