Machine-actionable metadata in practice: lessons from automating FAIR assessment in plant-pollinator datasets.
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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.
Presented at Living Data 2025, Bogotá, Colômbia.
Presented at Living Data 2025, Bogotá, Colômbia.
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