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Dettaglio pubblicazione

2023, Lecture Notes in Artificial Intelligence, Pages 88-101 (volume: 14318 LNAI)

Ontology-Based Data Management in Healthcare: The Case of the Italian Arthroplasty Registry (04b Atto di convegno in volume)

Valentini Riccardo, Carrani Eugenio, Torre Marina, Lenzerini Maurizio

Italian Arthroplasty Registry (Registro Italiano ArtroProtesi, RIAP) is organized as a federation of regional registries, involved on voluntary basis, with the purpose of collecting data to monitor joint prostheses safety and quickly recall patients in case of adverse events. Data collection flows may differ among the participating regions, therefore data have to be properly integrated in a single omnicomprehensive data repository. The aim of this paper is to report on the application of the Ontology Based Data Management (OBDM) approach in order to integrate, standardize and prepare data for analyses and for extracting pieces of information from the different flows converging to RIAP. From the point of view of Data Management, one of the distinguishing features of OBDM is to provide well-founded methods for data quality assessment, which is crucial also for subsequent machine learning tasks. From the knowledge representation point of view, the ontology constitutes a fundamental asset for giving proper semantics to concepts, relationships and rules regarding the arthroplasty domain, as determined by the expertise of the stakeholders. Thus, the whole approach improves the RIAP capabilities of handling data, dealing with complex research questions in the healthcare domain and sharing information with the international community of Arthroplasty Registries. Finally, the availability of a SPARQL endpoint to connect the central relational database to the RIAP ontology paves the way for enabling RIAP to publish open data with proper semantics.
ISBN: 978-3-031-47545-0; 978-3-031-47546-7
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