Correspondence Patterns for Ontology Alignment
EKAW '08 Proceedings of the 16th international conference on Knowledge Engineering: Practice and Patterns
OWSCIS: Ontology and Web Service Based Cooperation of Information Sources
SITIS '07 Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System
SPARQL query rewriting for implementing data integration over linked data
Proceedings of the 2010 EDBT/ICDT Workshops
Ontology mapping and SPARQL rewriting for querying federated RDF data sources
OTM'10 Proceedings of the 2010 international conference on On the move to meaningful internet systems: Part II
Querying semantic web data with SPARQL
Proceedings of the thirtieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Hi-index | 0.00 |
Electronic Health Records (EHRs) contain a rapidly increasing volume of data which is, in general, distributed in autonomous heterogeneous databases. An emerging trend is the secondary use of such data (in most cases anonymized for privacy reasons), for purposes other than healthcare, such as for generating accurate disorder epidemiology datasets, real world treatment progress assessment and patient selection for clinical trials among others. The structure and purpose of the EHRs pose significant limitations in the richness and the complexity of the questions to be posed. In fact, the latter case introduces a greater challenge; it requires that two different domains (in terms of semantics) need to be interlinked - clinical research and healthcare. This paper aims at presenting a novel SPARQL query rewriting mechanism as part of an ontology-based approach for interlinking clinical research with healthcare EHRs for supporting automatic selection of patients who satisfy the eligibility criteria of clinical trials.