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1000
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Abstract/Summary
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In the context of personalized medicine, long-term data collection allows researchers to track how diseases progress over time, identify patterns of environmental and genetic risk, and assess the impact of different treatment strategies. The project DATOS-CAT aims to increase the visibility and scientific impact of the population-based cohorts developed in Catalonia GCAT|Genomes for life and the COVICAT-CONTENT sub-cohort, and to contribute to the development of procedures applicable to other cohorts, improving the level of interoperability of their data in the context of the FAIR data ecosystem principles to facilitate their exploitation and scientific use. In this work we present Ontobridge, an ontology-based tool developed by the Hospital Clínic de Barcelona, for semantic data mapping between an ontology representing a source data model (eg. local EHR), and one or more ontologies, representing data standards to transform local databases into standards (eg. OMOP-CDM). We use Ontop to replicate source data model into RDFs through R2RML mappings. Local concepts are mapped to standard ones by means of the owl:sameAs property to allow for semantic interoperability, while the syntactic equivalence is performed by defining that local properties to be instances of metaclasses that model attributes of the target data model. These ontologies are loaded into a Jena Fuseki server, and the corresponding SPARQL queries are executed to generate the OMOP-CDM tables. This semantic approach allows the integration of vocabularies and ontologies not present in the OMOP vocabularies, and extend the standardization efforts into other models like OpenEHR or phenopackets.
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