
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 center managers in 2019 with the aim to build a common approach to describe what is observed, measured, calculated, or derived. Based on an extensive analysis of existing semantic representations of variables, the WG has recently published the I-ADOPT framework ontology to facilitate interoperability between existing semantic resources and support the provision of machine-readable variable descriptions whose components are mapped to FAIR vocabulary terms. The I-ADOPT framework ontology defines a set of high level semantic components that can be used to describe a variety of patterns commonly found in scientific observations. This contribution will focus on how the I-ADOPT framework can be applied to represent variables commonly used in the biodiversity domain.
submitted to S4BioDiv 2021: 3rd International Workshop on Semantics for Biodiversity, September 15, 2021, Bozen, Italy
FOS: Computer and information sciences, Computer Science - Artificial Intelligence, semantic interoperabil, variables, semantic interoperability, Artificial Intelligence (cs.AI), observations, observable properties, semantic interoperability FAIR terminology, biodiversity
FOS: Computer and information sciences, Computer Science - Artificial Intelligence, semantic interoperabil, variables, semantic interoperability, Artificial Intelligence (cs.AI), observations, observable properties, semantic interoperability FAIR terminology, biodiversity
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