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International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems

IEA/AIE 2016: Trends in Applied Knowledge-Based Systems and Data Science pp 373–385Cite as

A Survey on Ontologies and Ontology Alignment Approaches in Healthcare

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9799))

Abstract

In the era of Internet, high connectivity and openness introduced an opportunity for a new kind of approach to healthcare information system integration. Such an approach may utilize semantic-based technologies to represent and communicate knowledge between these systems. Resource Description Framework (RDF) in conjunction with Web Ontology Language (OWL) can be considered as a de facto standard when it comes to semantic web and linked data technologies, and represents a foundation for defining healthcare ontologies. The goal of this paper is to provide an overview and critical review of existing healthcare ontologies and approaches to healthcare IS integration, focusing on OWL/RDF based solutions. With this review we want to show that although a lot work is done in this area, no universal or omnipresent solution has surfaced to allow automatic or at least semi-automatic integration of healthcare ISs. As there is a large number of established and emerging ontologies covering this subject our review will not provide an exhaustive collection of all the references in the area, but present the most notable standards, ontologies, taxonomies, and integration approaches.

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Notes

  1. 1.

    https://www.w3.org/RDF/.

  2. 2.

    https://www.w3.org/2001/sw/wiki/OWL.

  3. 3.

    http://yosemitemanifesto.org/.

  4. 4.

    http://www.semantichealthnet.eu/.

  5. 5.

    http://www.opencimi.org/.

  6. 6.

    http://www.hl7.org/.

  7. 7.

    http://www.en13606.org/.

  8. 8.

    http://www.openehr.org/.

  9. 9.

    http://www.hl7.org/implement/standards/rim.cfm.

  10. 10.

    https://www.nlm.nih.gov/research/umls/Snomed/snomed_main.html.

  11. 11.

    https://hl7-fhir.github.io/index.html.

  12. 12.

    http://trajano.us.es/~isabel/EHR/.

  13. 13.

    http://sig.biostr.washington.edu/projects/fm/AboutFM.html.

  14. 14.

    https://ncit.nci.nih.gov/ncitbrowser/.

  15. 15.

    http://ws.nju.edu.cn/falcon-ao/.

  16. 16.

    https://github.com/AgreementMakerLight/AML-Jar.

  17. 17.

    Ontology Alignment Evaluation Initiative - http://oaei.ontologymatching.org/.

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Acknowledgments

This research is supported by the Ministry of Education, Science, and Technological Development of Republic of Serbia, Grant III–47003: “Infrastructure for technology enhanced learning in Serbia” and Grant III–44010: “Intelligent Systems for Software Product Development and Business Support based on Models.”.

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Authors and Affiliations

  1. Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Serbia

    Vladimir Dimitrieski, Aleksandar Kovačević & Ivan Luković

  2. Iwate Prefectural University, Takizawa, Iwate, Japan

    Gajo Petrović & Hamido Fujita

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  1. Vladimir Dimitrieski
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  2. Gajo Petrović
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  3. Aleksandar Kovačević
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  4. Ivan Luković
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  5. Hamido Fujita
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Corresponding author

Correspondence to Vladimir Dimitrieski .

Editor information

Editors and Affiliations

  1. Iwate Prefectural University , Iwate, Japan

    Hamido Fujita

  2. Department Computer Science, Texas State University, San Marcos, Texas, USA

    Moonis Ali

  3. Universiti Teknologi Malaysis (UTM), Bahru, Malaysia

    Ali Selamat

  4. Iwate Prefectural University , Iwate, Japan

    Jun Sasaki

  5. Iwate Prefectural University , Iwate, Japan

    Masaki Kurematsu

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Dimitrieski, V., Petrović, G., Kovačević, A., Luković, I., Fujita, H. (2016). A Survey on Ontologies and Ontology Alignment Approaches in Healthcare. In: Fujita, H., Ali, M., Selamat, A., Sasaki, J., Kurematsu, M. (eds) Trends in Applied Knowledge-Based Systems and Data Science. IEA/AIE 2016. Lecture Notes in Computer Science(), vol 9799. Springer, Cham. https://doi.org/10.1007/978-3-319-42007-3_32

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  • DOI: https://doi.org/10.1007/978-3-319-42007-3_32

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