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SPARQL is a standard query language for RDF data that are commonly used to represent and store Semantic Web data. There are a lot of SPARQL endpoints to retrieve and see the data by SPARQL queries. Although it greatly helps us query semantic data with ontologies, their diversity of ontologies make it difficult to query the data without understanding of their target ontologies. Although it is possible to use ontology mapping techniques to convert a query based on an ontology to another one based on another ontology, it is assumed to be able to define complete mappings among the two ontologies without any loss of their semantics. In this paper, we present an approach about SPARQL query rewriting when ontology mappings are not complete. We show a way of rewriting a SPARQL query with one ontology to another query on a different ontology when we can specify an ordering based on their mapping reliability. [ABSTRACT FROM PUBLISHER]

The Los Angeles Data Resource (LADR) is a joint project of major Los Angeles health care provider organizations. The LADR helps clinical investigators to explore the size of potential research study cohorts using operational clinical data across all participating institutions. The Charles R. Drew University of Medicine and Science (CDU) LADR team sought to develop an innovative data architecture that would aggregate de-identified clinical data from safety-net providers in the community into CDU LADR node. This in turn would be federated with the other nodes of LADR for a shared view in a way that was never available before. This led to a selfservice system to assess patients matching study criteria at each medical center and to search patients by demographics, ICD-9 codes, lab results and medications. [ABSTRACT FROM AUTHOR]