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An approach for sub-ontology evolution in a distributed health care enterprise
Department of Computer Science and Computer Engineering, La Trobe University, Victoria, Australia; Department of Computer Science and Electronics, Gadjah Mada University, Yogyakarta, Indonesia.
Department of Computer Science and Computer Engineering, La Trobe University, Victoria, Australia.
SFB/TR 8 Spatial Cognition, Informatics, University of Bremen, Bremen, Germany. (AASS)ORCID iD: 0000-0002-6290-5492
2013 (English)In: Information Systems, ISSN 0306-4379, E-ISSN 1873-6076, Vol. 38, no 5, p. 727-744Article in journal (Refereed) Published
Abstract [en]

In response to the changing nature of health issues, standardized health ontologies such as SNOMED CT and UMLS incline to change more frequently than most other domain ontologies. Yet, semantic interoperability shared among institutions within a distributed health care enterprise relies heavily on the availability of a valid and up-to-date standardized ontology. In this paper, we propose the creation and preservation of sub-ontologies to deal with the frequent changes in health ontologies. Our approach focuses on the nature and characteristics of standard health ontologies, however it can also be applied to other domain ontologies with similar characteristics. Our sub-ontology evolution approach defines ways to create valid sub-ontologies for each specific health application, and to effectively develop a series of propagation mechanism when the main ontology changes. Our approach will (i) isolate the required change propagation to the relevant health applications that utilized the changing concepts only, and (ii) optimize the propagation mechanism to include the minimum number of operations only. Since a sub-ontology should be a valid ontology by itself, the change propagation approach used in this process should contain the rules to assure the validity of the produced sub-ontology while keeping the consistency of the sub-ontology to the evolved base ontology. A change identification process, which considers the nature of the health ontology change logs, is conducted to identify the semantics of the changes. From the evaluation, it is shown that the content of the evolved sub-ontologies produced using our approach is consistent to the evolved base ontology. Moreover, the propagation process can be performed more efficiently because the number of operations required for our change propagation method is lower than the number of operations required for direct re-extraction from the evolved base ontology.

Place, publisher, year, edition, pages
Elsevier, 2013. Vol. 38, no 5, p. 727-744
Keywords [en]
Ontology evolution; Change propagation; Sub-ontology; Health; Semantics of change
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:oru:diva-64234DOI: 10.1016/j.is.2012.03.006ISI: 000317539100006Scopus ID: 2-s2.0-84893009156OAI: oai:DiVA.org:oru-64234DiVA, id: diva2:1174494
Note

Funding Agency:

Ministry of National Education of the Republic of Indonesia

Available from: 2018-01-15 Created: 2018-01-15 Last updated: 2018-01-17Bibliographically approved

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Publisher's full textScopushttps://doi.org/10.1016/j.is.2012.03.006

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Bhatt, Mehul

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