Mapping bread wheat trait ontologies for semantic interoperability
2024
Nédellec, Claire | Aubin, Sophie | Sauvion, Clara | Ibanescu, Liliana | Bravo, Sonia | Le-Gouis, Jacques | Marcel, Thierry, C | Pommier, Cyril | Bossy, Robert | Alaux, Michael | Mathématiques et Informatique Appliquées du Génome à l'Environnement [Jouy-En-Josas] (MaIAGE) ; Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Direction pour la Science Ouverte (DipSO) ; Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Mathématiques et Informatique Appliquées (MIA Paris-Saclay) ; AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Génétique Diversité et Ecophysiologie des Céréales (GDEC) ; Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA) | BIOlogie et GEstion des Risques en agriculture (BIOGER) ; Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Unité de Recherche Génomique Info (URGI) ; Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | IR BioInfOmics ; Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | ANR-18-CE23-0017,D2KAB,Des Données aux Connaissances en Agronomie et Biodiversité(2018)
International audience
显示更多 [+] 显示较少 [-]英语. The Wheat Crop ontology was created to annotate phenotypic experimental data (i.e. field and greenhouse measurements standardized and integrated in databases). The Wheat Trait and Phenotype ontology was created to annotate information on wheat traits from the literature (i.e. text found in the abstract, results and discussion of scholarly articles). To enable seamless data retrieval on wheat traits from these complementary sources, the classes in the two ontologies have been aligned. All pairs of ontology classes were examined and categorized in nine groups based on the nature of their relationships (e.g. equivalence, subsumption). General principles emerged from this process which were formalized into rules. The Simple Standard for Sharing Ontological Mappings (SSSOM) representation was chosen to represent the mappings in RDF (Resource Description Framework), including their metadata such as creators, reviewers, and justification (including rules).The mapping dataset is publicly available. It covers 77% of the ontology classes. Most labels of the aligned classes differed significantly and required domain expertise for decisions, especially for traits related to biotic stress. Consequently, most mappings are close mappings rather than exact equivalents. We present the end-to-end manual process used to select and represent mappings in SSSOM within the specific domain of wheat traits. We derive general lessons from the complex alignment process that extend beyond the specific case of these two ontologies and more generally apply to alignments of specialized ontologies for information retrieval purposes. This work demonstrates the relevance of SSSOM for representing these mappings.
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