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Querying clinical data in HL7 RIM based relational model with morph-RDB.
Priyatna, Freddy; Alonso-Calvo, Raul; Paraiso-Medina, Sergio; Corcho, Oscar.
Afiliación
  • Priyatna F; Ontology Engineering Group, Universidad Politécnica de Madrid, Madrid, Spain. fpriyatna@fi.upm.es.
  • Alonso-Calvo R; Biomedical Informatics Group, Universidad Politécnica de Madrid, Madrid, Spain.
  • Paraiso-Medina S; Biomedical Informatics Group, Universidad Politécnica de Madrid, Madrid, Spain.
  • Corcho O; Ontology Engineering Group, Universidad Politécnica de Madrid, Madrid, Spain.
J Biomed Semantics ; 8(1): 49, 2017 Oct 05.
Article en En | MEDLINE | ID: mdl-28982381
ABSTRACT

BACKGROUND:

Semantic interoperability is essential when carrying out post-genomic clinical trials where several institutions collaborate, since researchers and developers need to have an integrated view and access to heterogeneous data sources. One possible approach to accommodate this need is to use RDB2RDF systems that provide RDF datasets as the unified view. These RDF datasets may be materialized and stored in a triple store, or transformed into RDF in real time, as virtual RDF data sources. Our previous efforts involved materialized RDF datasets, hence losing data freshness.

RESULTS:

In this paper we present a solution that uses an ontology based on the HL7 v3 Reference Information Model and a set of R2RML mappings that relate this ontology to an underlying relational database implementation, and where morph-RDB is used to expose a virtual, non-materialized SPARQL endpoint over the data.

CONCLUSIONS:

By applying a set of optimization techniques on the SPARQL-to-SQL query translation algorithm, we can now issue SPARQL queries to the underlying relational data with generally acceptable performance.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Programas Informáticos / Bases de Datos Factuales / Almacenamiento y Recuperación de la Información / Ontologías Biológicas Límite: Humans Idioma: En Revista: J Biomed Semantics Año: 2017 Tipo del documento: Article País de afiliación: España

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Programas Informáticos / Bases de Datos Factuales / Almacenamiento y Recuperación de la Información / Ontologías Biológicas Límite: Humans Idioma: En Revista: J Biomed Semantics Año: 2017 Tipo del documento: Article País de afiliación: España