Título:	Machine-actionable metadata in practice: lessons from automating FAIR assessment in plant-pollinator datasets.
Autor:	DRUCKER, D. P. SOARES, F. M. POELEN, J. SALIM, J. A.
Afiliación:	DEBORA 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.
Año:	2025
Referencia:	Biodiversity Information Science and Standards, v. 9, e180280, 2025.
Descripción:	We 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.
Palabras clave:	Metadados Datasets de polinizador de plantas Prinícpios FAIR Interações bióticas Interoperabilidade Revisão de dados Publicação de dados Biotic interactions Interoperability Data review Data publication
DOI:	https://doi.org/10.3897/biss.9.180280
Notas:	Presented at Living Data 2025, Bogotá, Colômbia.
Tipo de Material:	Resumo em anais e proceedings
Acceso:	openAccess
Aparece en las colecciones:	Resumo em anais de congresso (CNPTIA)