ANGEL ESTEBAN GIL, JESUALDO TOMÁS FERNÁNDEZ BREIS, MARTIN BOEKER,

• [GI/IMIB/E170/2011] TECNOLOGÍAS DE MODELADO, PROCESAMIENTO Y GESTIÓN DEL CONOCIMIENTO

Regional and epidemiological cancer registries are important for cancer research and the quality management of cancer treatment. Many technological solutions are available to collect and analyse data for cancer registries nowadays, however, the lack of a well-defined common semantic model is a problem when user defined analyses and linking data to external resources are required. The main objective of this study is the development of a Semantic Web platform that facilitates the analysis and visualization of data from cancer registries including (1) the representation of the disease course of a patient, (2) the representation of the aggregated disease courses of a group of patients, and (3) the definition of customizable dashboards for patient selection and visualization of the data.

We have designed a semantic model for local cancer registries and implemented it with semantic web technology in a feasibility study. Our proposal is based on our previous results and experience working with semantic technologies. Data stored in a cancer registry database were transformed into RDF employing a process driven by OWL ontologies. The semantic representation of the data was then processed to extract semantic patient profiles, which were exploited by means of SPARQL queries to identify groups of similar patients and to analyze the disease timelines of patients.

Based on the requirements analysis, an OWL ontology that models the semantics of an institutional cancer registry in a pragmatic extensible wayhas been developed. Based on this model, we have implemented a Semantic Web platform that allows transforming and storing data from cancer registries in RDF repositories. With a graphical user interface of this platform, users can also formulate incremental user-defined queries. The query results can be displayed in several customizable ways. The complex timeline of the disease of individual patients can be clearly represented. Different events, e.g. different therapies and courses of the disease, are presented according to their temporal and causal relations. Moreover, the semantic structure of the representation renders it easy to analyse key figures on aggregate patient level. We have applied our approach using the requirements of the cancer registry of the Comprehensive Cancer Center Freiburg (CCCF) and used simulated data (207.190 patients) to generate a semantic repository. A prototype web platform (http://sele.inf.um.es/SECARE/) has been implemented demonstrating appropriate functionality and performance. The same methodology has been applied in a study with real data from the Colorectal Cancer Prevention Program of the Region of Murcia with 322.869 patients (http://sele.inf.um.es/SECOLON/).

This work has demonstrated that ontologies and the RDF repositories can be effectively combined for exploiting a local cancer registry. On the one hand, we constructed an ontology that models the knowledge of local cancer registry. On the other hand, we have used semantic web technologies for building a platform to analyse the complex timelines of patients with cancer. Besides, our semantic structure has allowed for representing the aggregated disease timelines of patient groups.