Representing human expertise by the OWL web ontology language to support knowledge engineering in decision support systems

Asia Ramzan*, Hai Wang, Christopher Buckingham

*Corresponding author for this work

Research output: Chapter in Book/Published conference outputConference publication

Abstract

Clinical decision support systems (CDSSs) often base their knowledge and advice on human expertise. Knowledge representation needs to be in a format that can be easily understood by human users as well as supporting ongoing knowledge engineering, including evolution and consistency of knowledge. This paper reports on the development of an ontology specification for managing knowledge engineering in a CDSS for assessing and managing risks associated with mental-health problems. The Galatean Risk and Safety Tool, GRiST, represents mental-health expertise in the form of a psychological model of classification. The hierarchical structure was directly represented in the machine using an XML document. Functionality of the model and knowledge management were controlled using attributes in the XML nodes, with an accompanying paper manual for specifying how end-user tools should behave when interfacing with the XML. This paper explains the advantages of using the web-ontology language, OWL, as the specification, details some of the issues and problems encountered in translating the psychological model to OWL, and shows how OWL benefits knowledge engineering. The conclusions are that OWL can have an important role in managing complex knowledge domains for systems based on human expertise without impeding the end-users' understanding of the knowledge base. The generic classification model underpinning GRiST makes it applicable to many decision domains and the accompanying OWL specification facilitates its implementation.

Original languageEnglish
Title of host publicationInnovation in Medicine and healthcare 2014
EditorsManuel Graña, Carlos Toro, Robert J. Howlett, Lakhmi C. Jain
PublisherIOS
Pages290-299
Number of pages10
ISBN (Electronic)978-1-61499-474-9
ISBN (Print)978-1-61499-473-2
DOIs
Publication statusPublished - 1 Jan 2014
Event2nd KES international conference on Innovation in Medicine and healthcare - San Sebastian, Spain
Duration: 9 Jul 201411 Jul 2014

Publication series

NameStudies in health technology and informatics
PublisherIOS
Volume207

Conference

Conference2nd KES international conference on Innovation in Medicine and healthcare
Abbreviated titleInMed-14
CountrySpain
CitySan Sebastian
Period9/07/1411/07/14

Keywords

  • clinical decision support system
  • fuzzy sets
  • knowledge engineering
  • OWL

Fingerprint

Dive into the research topics of 'Representing human expertise by the OWL web ontology language to support knowledge engineering in decision support systems'. Together they form a unique fingerprint.
  • Handling varying amounts of missing data when classifying mental-health risk levels

    Saleh, S. N. & Buckingham, C. D., 31 Dec 2014, Innovation in Medicine and healthcare 2014. Graña, M., Toro, C., Howlett, R. J. & Jain, L. C. (eds.). IOS, p. 92-101 10 p. (Studies in health technology and informatics; vol. 207).

    Research output: Chapter in Book/Published conference outputConference publication

  • Understanding data collection behaviour of mental health practitioners

    Rezaei-Yazdi, A. & Buckingham, C. D., 31 Dec 2014, Innovation in Medicine and healthcare 2014. Graña, M., Toro, C., Howlett, R. J. & Jain, L. C. (eds.). IOS, p. 193-202 10 p. (Studies in health technology and informatics; vol. 207).

    Research output: Chapter in Book/Published conference outputConference publication

Cite this