The I-ADOPT Interoperability Framework for FAIRer data descriptions of biodiversity
Barbara Magagna, Ilaria Rosati, Maria Stoica, Sirko Schindler, and Gwenaelle Moncoiffe, Anusuriya Devaraju, Johannes Peterseil and, Robert Huber

TL;DR
The paper presents the I-ADOPT framework ontology, a semantic tool designed to improve interoperability and FAIR data descriptions for biodiversity observations and variables across diverse data sources.
Contribution
It introduces the I-ADOPT framework ontology, enabling standardized, machine-readable descriptions of biodiversity variables to enhance data interoperability.
Findings
Published the I-ADOPT framework ontology for biodiversity data.
Demonstrated how the framework supports interoperability of semantic resources.
Facilitates FAIR-compliant, machine-readable biodiversity data descriptions.
Abstract
Biodiversity, the variation within and between species and ecosystems, is essential for human well-being and the equilibrium of the planet. It is critical for the sustainable development of human society and is an important global challenge. Biodiversity research has become increasingly data-intensive and it deals with heterogeneous and distributed data made available by global and regional initiatives, such as GBIF, ILTER, LifeWatch, BODC, PANGAEA, and TERN, that apply different data management practices. In particular, a variety of metadata and semantic resources have been produced by these initiatives to describe biodiversity observations, introducing interoperability issues across data management systems. To address these challenges, the InteroperAble Descriptions of Observable Property Terminology WG (I-ADOPT WG) was formed by a group of international terminology providers and data…
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Taxonomy
TopicsBiomedical Text Mining and Ontologies · Semantic Web and Ontologies · Species Distribution and Climate Change
