The BEAT-COVID project in the LUMC is created to do research to understand the pathophysiology of COVID-19 disease and to improve precision diagnosis and intervention to win the battle with SARS-CoV-2 virus.The project is composed of several stakeholders from physicians, data managers to researchers to coordinate for efficient research in four groups.
From the group of 'Big data' we are working on the FAIRification of the patient observational data to enable efficient research. Our approach is based on the use of ontological models to link data and to describe datasets. Our method uses Semantic Web technologies such as Internationalized Resource Identifiers (IRIs), Web Ontology Language (OWL) ontologies, Resource Description Framework (RDF) data structure or the SPARQL query language.
In the fair-data-model directory is the ontological model work to link different clinical data. Our first ontological model is within the cytokine subdirectory, and links cytokines lab measurements, biosamples and score phenotypes.
Project Scripts under this folder and recursive subfolders are licensed under the terms of the MIT License.
Project Data under this folder and recursive subfolders are licensed under the terms of the CC0 License.