Implementing a new Research Data Alliance recommendation, the I-ADOPT framework, for the naming of environmental variables of continental surfaces - PEPR OneWater
Article Dans Une Revue Earth Science Informatics Année : 2024

Implementing a new Research Data Alliance recommendation, the I-ADOPT framework, for the naming of environmental variables of continental surfaces

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Abstract To improve data usage in an interdisciplinary context, a clear understanding of the variables being measured is required for both humans and machines. In this paper, the I-ADOPT framework, which decomposes variable names into atomic elements, was tested within the context of continental surfaces and critical zone science, characterized by a large number and variety of observed environmental variables. We showed that the I-ADOPT framework can be used effectively to describe environmental variables with precision and that it was flexible enough to be used in the critical zone science context. Variable names can be documented in detail while allowing alignment with other ontologies or thesauri. We have identified difficulties in modeling complex variables, such as those monitoring fluxes between different environmental compartments and for variables monitoring ratios of physical quantities. We also showed that, for some variables, different decompositions were possible, which could make alignments with other ontologies and thesauri more difficult. The precision of variable names proved inadequate for data discovery services and a non-standard label ( SimplifiedLabel ) had to be defined for this purpose. In the context of open science and interdisciplinary research, the I-ADOPT framework has the potential to improve the interoperability of information systems and the use of data from various sources and disciplines.
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hal-04631839 , version 1 (02-07-2024)

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Coussot Charly, Chaffard Véronique, Boudevillain Brice, Sylvie Galle, Braud Isabelle. Implementing a new Research Data Alliance recommendation, the I-ADOPT framework, for the naming of environmental variables of continental surfaces. Earth Science Informatics, 2024, ⟨10.1007/s12145-024-01373-9⟩. ⟨hal-04631839⟩
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