Semantic Representation of Preclinical Data in Radiation Oncology.

Background : In radiation oncology, the data generated from preclinical trials serve as initial validation for treatment effectiveness and optimizing clinical approaches by unraveling molecular mechanisms underlying different treatment responses. Therefore, it is important to standardize the practice in managing preclinical trial data to ensure consistency and reproducibility across studies, promoting collaboration, and facilitating regulatory review. The primary goal of this work is to standardize the representation of data collected from preclinical radiobiology and radiation oncology studies as a way to facilitate knowledge discovery. To achieve this goal, we combined ontology with semantic Web techniques to publish mapped data and easily query them using SPARQL Protocol and RDF Query Language (SPARQL). Results : We expanded the Radiation Oncology Ontology (ROO) to include terminology related to the exposure of animal models to treatment, animal model’s demographic characteristics; as well as clinical information in live animals. The extended ROO contains 123 new entities (89 classes, 29 data properties and 5 object properties). We combined the extended ontology with Semantic Web technologies to demonstrate how to integrate and query data from different relational databases. Discussion : The use of ontologies and semantic web tools are a way to comply to the FAIR principles. FAIR preclinical data improve collaboration, transparency, and reproducibility in radiotherapy research.