Towards Semantic Interoperability Among Heterogeneous Cancer Data Models Using a Layered Modular Hyper-Ontology
Mirna El Ghosh, Varvara Kalokyri, Mélanie Sambres, Morgan Vaterkowski, Catherine Duclos, Xavier Tannier, Gianna Tsakou, Manolis Tsiknakis, Christel Daniel, Ferdinand Dhombres · Frontiers in artificial intelligence and applications · 2024
Semantic interoperability is a growing and challenging subject in the healthcare domain. It aims to ensure a coherent and unambiguous exchange, use, and reuse of health information among different systems and applications. In the context of the EUCAIM (Cancer Image Europe) project, semantic interoperability among various heterogeneous cancer image data models is required to support the communication, integration, and sharing of data in a standardized and structured way. For this purpose, hyper-ontology is developed as a common semantic meta-model that bridges the disparate imaging and clinical knowledge of the various repositories in EUCAIM and supports their integration. EUCAIM’s hyper-ontology is also an application-based ontology targeted for federated semantic querying and image annotation. To facilitate the hyper-ontology building process and ensure the extensibility of the ontology model, an iterative hybrid well-founded approach that divides the ontology structure into layers and modules is established.