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J Biomed Inform. 2016 Aug;62:243-64. doi: 10.1016/j.jbi.2016.07.011. Epub 2016 Jul 8.

Publication, discovery and interoperability of Clinical Decision Support Systems: A Linked Data approach.

Author information

1
Norwegian Centre for e-Health Research, University Hospital of North Norway, P.O. Box 35, N-9038 Tromsø, Norway; Department of Clinical Medicine, Faculty of Health Sciences, UIT The Arctic University of Norway, 9037 Tromsø, Norway. Electronic address: Luis.Marco.Ruiz@telemed.no.
2
Knowledge Media Institute, The Open University Walton Hall, Milton Keynes MK7 6AA, UK.
3
Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain; Veratech for Health SL, Doctor Lluch 299, 46011 Valencia, Spain.
4
Department of Learning, Informatics, Management and Ethics, Karolinska Institutet, Tomtebodavägen 18, SE 17177 Stockholm, Sweden.
5
Norwegian Centre for e-Health Research, University Hospital of North Norway, P.O. Box 35, N-9038 Tromsø, Norway; Department of Clinical Medicine, Faculty of Health Sciences, UIT The Arctic University of Norway, 9037 Tromsø, Norway.

Abstract

BACKGROUND:

The high costs involved in the development of Clinical Decision Support Systems (CDSS) make it necessary to share their functionality across different systems and organizations. Service Oriented Architectures (SOA) have been proposed to allow reusing CDSS by encapsulating them in a Web service. However, strong barriers in sharing CDS functionality are still present as a consequence of lack of expressiveness of services' interfaces. Linked Services are the evolution of the Semantic Web Services paradigm to process Linked Data. They aim to provide semantic descriptions over SOA implementations to overcome the limitations derived from the syntactic nature of Web services technologies.

OBJECTIVE:

To facilitate the publication, discovery and interoperability of CDS services by evolving them into Linked Services that expose their interfaces as Linked Data.

MATERIALS AND METHODS:

We developed methods and models to enhance CDS SOA as Linked Services that define a rich semantic layer based on machine interpretable ontologies that powers their interoperability and reuse. These ontologies provided unambiguous descriptions of CDS services properties to expose them to the Web of Data.

RESULTS:

We developed models compliant with Linked Data principles to create a semantic representation of the components that compose CDS services. To evaluate our approach we implemented a set of CDS Linked Services using a Web service definition ontology. The definitions of Web services were linked to the models developed in order to attach unambiguous semantics to the service components. All models were bound to SNOMED-CT and public ontologies (e.g. Dublin Core) in order to count on a lingua franca to explore them. Discovery and analysis of CDS services based on machine interpretable models was performed reasoning over the ontologies built.

DISCUSSION:

Linked Services can be used effectively to expose CDS services to the Web of Data by building on current CDS standards. This allows building shared Linked Knowledge Bases to provide machine interpretable semantics to the CDS service description alleviating the challenges on interoperability and reuse. Linked Services allow for building 'digital libraries' of distributed CDS services that can be hosted and maintained in different organizations.

KEYWORDS:

Clinical Decision Support; Linked Data; Medical ontologies; Semantic Web Service; Semantic interoperability; Service Oriented Architecture

PMID:
27401856
DOI:
10.1016/j.jbi.2016.07.011
[Indexed for MEDLINE]
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