Machine-actionable metadata in practice: lessons from automating FAIR assessment in plant-pollinator datasets.

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dc.contributorDEBORA PIGNATARI DRUCKER, CNPTIA; FILIPI MIRANDA SOARES, NATIONAL RESEARCH INSTITUTE FOR AGRICULTURE, FOOD AND THE ENVIRONMENT (FRANCE); JORRIT POELEN, RONIN INSTITUTE; JOSÉ AUGUSTO SALIM, UNIVERSIDADE DE SÃO PAULO.
dc.creatorDRUCKER, D. P.
dc.creatorSOARES, F. M.
dc.creatorPOELEN, J.
dc.creatorSALIM, J. A.
dc.date2025-12-04T17:48:40Z
dc.date2025-12-04T17:48:40Z
dc.date2025-12-03
dc.date2025
dc.date.accessioned2026-07-07T04:18:27Z
dc.descriptionWe developed a semi-automated workflow to assist in evaluating datasets against the FAIR principles using tools from the Global Biotic Interactions initiative (GloBI, Poelen et al. 2014). The GloBI bots "Nomer" and "Elton" can read structured metadata from standard vocabularies such as Darwin Core (DwC), Ecological Metadata Language (EML), and the Plant-Pollinator Interactions (PPI) vocabulary. Nomer focuses on taxonomic alignment with several taxonomic catalogues, such as GBIF Backbone and Catalogue of Life. Elton extracts species interactions from datasets of various structures and formats, including DwC-Archives.
dc.descriptionPresented at Living Data 2025, Bogotá, Colômbia.
dc.identifierBiodiversity Information Science and Standards, v. 9, e180280, 2025.
dc.identifierhttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1182227
dc.identifierhttps://doi.org/10.3897/biss.9.180280
dc.identifier.urihttp://hdl.handle.net/123456789/457253
dc.languageeng
dc.rightsopenAccess
dc.subjectMetadados
dc.subjectDatasets de polinizador de plantas
dc.subjectPrinícpios FAIR
dc.subjectInterações bióticas
dc.subjectInteroperabilidade
dc.subjectRevisão de dados
dc.subjectPublicação de dados
dc.subjectBiotic interactions
dc.subjectInteroperability
dc.subjectData review
dc.subjectData publication
dc.titleMachine-actionable metadata in practice: lessons from automating FAIR assessment in plant-pollinator datasets.
dc.typeResumo em anais e proceedings

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