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dc.contributor.authorDunn, Robert
dc.contributor.authorLief, Christina
dc.contributor.authorPeng, Ge
dc.contributor.authorWright, William
dc.contributor.authorBaddour, Omar
dc.contributor.authorDonat, Markus
dc.contributor.authorDubuisson, Brigitte
dc.contributor.authorLegeais, Jean-François
dc.contributor.authorSiegmund, Peter
dc.contributor.authorSilveira, Reinaldo
dc.contributor.authorWang, Xiaolan L.
dc.contributor.authorZiese, Markus
dc.contributor.otherBarcelona Supercomputing Center
dc.date.accessioned2021-03-25T16:47:47Z
dc.date.available2021-03-25T16:47:47Z
dc.date.issued2021
dc.identifier.citationDunn, R. [et al.]. Stewardship maturity assessment tools for modernization of climate data management. "Data Science Journal", 2021, vol. 20, núm. 1.
dc.identifier.issn1683-1470
dc.identifier.urihttp://hdl.handle.net/2117/342469
dc.description.abstractHigh quality and well-managed climate data are the cornerstone of all climate services. Consistently assessing how well the data are managed is one way to establish or demonstrate the trustworthiness of the data. This paper presents the World Meteorological Organization’s (WMO) Stewardship Maturity Matrix for Climate Data (SMM-CD) and the subsidiary SMM-CD for National and Regional Purposes (SMM-CD_NRP). Both these matrices have been developed with the support of the WMO and its High-Quality Global Data Management Framework for Climate (HQ-GDMFC). These self-assessment tools enable data managers to discover WMO recommended data stewardship practices, determine a roadmap for future development and improvement, as well as compare their process against other data providers. Datasets which have been maturity assessed are included in the WMO Climate Data Catalogue, where users can include the results of these maturity assessments into their decision-making process. The SMM-CD contains four categories (data access, usability and usage, quality management, and data management) each of which has a number of aspects, with scores assigned to one of five levels. A smaller number of categories in the SMM-CD_NRP are assigned to four levels appropriate for operationally produced datasets which are national or regional in scope. We explore a number of case studies where these matrices have been applied, as well as supply links to where the Guidance Documents and Assessment Templates (which may be updated) can be found.
dc.description.sponsorshipRobert Dunn was supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra. Ge Peng was supported by NOAA National Centers for Environmental Information (NCEI) through the Cooperative Institute for Satellite Earth System Studies (CISESS) under Cooperative Agreement NA19NES4320002. Markus Donat was supported by the Spanish Ministry for the Economy, Industry and Competitiveness, grant reference RYC-2017-22964. KNMI hosted the EIG-CDM workshop and the development and maintenance of the WMO Catalogue for Climate Data.
dc.format.extent20 p.
dc.language.isoeng
dc.publisherUbiquity Press [
dc.rightsAttribution 3.0 Spain
dc.rightsAttribution 4.0 International (CC BY 4.0)
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectÀrees temàtiques de la UPC::Enginyeria agroalimentària::Ciències de la terra i de la vida::Climatologia i meteorologia
dc.subject.lcshData sets
dc.subject.lcshWorld Meteorological Organization
dc.subject.lcshEarth sciences
dc.subject.otherData Stewardship
dc.subject.otherData Preservation
dc.subject.otherData Accessibility
dc.subject.otherData Usability
dc.subject.otherInformation Quality
dc.subject.otherMaturity Matrix
dc.subject.otherMetadata
dc.titleStewardship maturity assessment tools for modernization of climate data management
dc.typeArticle
dc.subject.lemacConjunts de dades
dc.identifier.doi10.5334/dsj-2021-007
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://datascience.codata.org/articles/10.5334/dsj-2021-007/#
dc.rights.accessOpen Access
dc.description.versionPostprint (published version)
local.citation.publicationNameData Science Journal
local.citation.volume20
local.citation.number1


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