Ontology Based Information Extraction for Disease Intelligence

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Prabath Chaminda Abeysiriwardana, Saluka R Kodituwakku
Published Date:
November 05, 2012
Volume 2, Issue 6
7 - 19

disease intelligence, disease ontology, information extraction, semantic web
Prabath Chaminda Abeysiriwardana, Saluka R Kodituwakku, "Ontology Based Information Extraction for Disease Intelligence". International Journal of Research in Computer Science, 2 (6): pp. 7-19, November 2012. doi:10.7815/ijorcs.26.2012.051 Other Formats


Disease Intelligence (DI) is based on the acquisition and aggregation of fragmented knowledge of diseases at multiple sources all over the world to provide valuable information to doctors, researchers and information seeking community. Some diseases have their own characteristics changed rapidly at different places of the world and are reported on documents as unrelated and heterogeneous information which may be going unnoticed and may not be quickly available. This research presents an Ontology based theoretical framework in the context of medical intelligence and country/region. Ontology is designed for storing information about rapidly spreading and changing diseases with incorporating existing disease taxonomies to genetic information of both humans and infectious organisms. It further maps disease symptoms to diseases and drug effects to disease symptoms. The machine understandable disease ontology represented as a website thus allows the drug effects to be evaluated on disease symptoms and exposes genetic involvements in the human diseases. Infectious agents which have no known place in an existing classification but have data on genetics would still be identified as organisms through the intelligence of this system. It will further facilitate researchers on the subject to try out different solutions for curing diseases.

  1. Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The Semantic Web. Scientific American, 284, 34-43.
  2. Visser, P.R.S., van Kralingen, R.W. and Bench-Capon, T.J.M. (1997) A method for the development of legal knowledge systems. In Proceedings of the Sixth International Conference on Artificial Intelligence and Law (ICAIL‟97), Melbourne, Australia.
  3. Introduction to Semantic Web - (Tutorial) - 2011 Semantic Technologies Conference - 6th of June, 2011, San Francisco, CA, USA - Ivan Herman, W3C )
  4. OWL Working Group. Available: http://www.w3.org /2007/OWL/wiki/OWL_Working_Group (Accessed 29 May 2011).
  5. OWL 2 Web Ontology Language Primer. Available: http://www.w3.org/TR/2009/REC-owl2-primer-20091027/ (Accessed 19 May 2011).
  6. Universal Resource Identifiers -- Axioms of Web Architecture. Available: http://www.w3.org/DesignIssues /Axioms.html - Tim Berners-Lee - December 19, 1996 (Accessed 15 May 2011).
  7. Resource Description Framework (RDF). Available. http://www.w3.org/RDF (Accessed 19 June 2011).
  8. OWL 2 Web Ontology Language Primer. Available: http://www.w3.org/TR/2009/REC-owl2-primer-20091027/ (Accessed 19 June 2011).
  9. SNOMED CT. Available: http://www.ihtsdo.org /index.php?id=snomed-ct0 (Accessed 9 June 2011).
  10. An Introduction to the Gene Ontology. Available: http://geneontology.org/GO.doc.shtml (Accessed 15 June 2011).
  11. About NCBO. Available: http://www.bioontology.org /about-ncbo (Accessed 15 June 2011).
  12. Ruttenberg, A., Clark, T., Bug, W., Samwald, M., Bodenreid-er, O., Chen, H., et al. (2007). Advancing translational research with the Semantic Web. BMC bioinformatics, 8 Suppl 3, S2. doi: 10.1186/1471-2105-8-S3-S2
  13. Semantic Web Health Care and Life Sciences (HCLS) Interest Group. Available: http://www.w3.org/2001 /sw/hcls/ (Accessed 6 May 2011).
  14. Du montier, M., & Villanueva-Rosales, N. (2009). Towards pharmacogenomics knowledge discovery with the semantic web. Briefings in Bioinformatics, 10(2), 153-163.
  15. Annotating the human genome with Disease Ontology. Available: http://www.biomedcentral.com/1471-2164/10/S1/S6 (Accessed 9 May 2011).
  16. Medical Subject Headings (MeSH®). Available: http://www.nlm.nih.gov/pubs/factsheets/mesh.html (Accessed 14 May 2011).
  17. PubMed Help. Available: http://www.ncbi.nlm.nih.gov /books/NBK3827/#pubmedhelp.PubMed_Quick_Start (Accessed 10 May 2011).
  18. http://www.nlm.nih.gov/pubs/factsheets/medline.html (Accessed 19 May 2011).
  19. Uschold, M. and King, M. (1995) Towards a methodology for building ontologies. In Workshop on Basic Ontological Issues in Knowledge Sharing, held in conjunction with IJCAI-95, Montreal, Canada. doi: 10.1017/S0269888900007797
  20. Gruninger, M. and Fox, M.S. (1995). Methodology for the Design and Evaluation of Ontologies. In: Proceedings of the Workshop on Basic Ontological Issues in Knowledge Sharing, IJCAI-95, Montreal.
  21. Uschold, M. and Gruninger, M. (1996). Ontologies: Principles, Methods and Applications.
  22. Bernaras, A. Laresgoiti, I. and Corera, J. (1996) Building and reusing ontologies for electrical network applications. In Proceedings of the European Conference on Artificial Intelligence ECAI-96.
  23. Gomez-Perez, A. (1996) A framework to verify knowledge sharing technology. doi: 10.1016/S0957-4174(96)00067-X
  24. Guarino, N. and Welty, C. (2000) identity, unity, and individuality: towards a formal toolkit for ontological analysis. Proceedings of ECAI-2000, August.
  25. Uschold, M. et.al. The Enterprise Ontology The Knowledge Engineering Review, Vol.13, Special Issue on Putting Ontologies to Use (eds. Mike Uschold and Austin Tate), (1998). Also available from AIAI as AIAITR-195 at: http://www.aiai.ed.ac.uk/~entprise/ enterprise/ontology.html
  26. Fox, M. et.al. "An Organisation Ontology for Enterprise Modeling", In Simulating Organizations: Computational Models of Institutions and Groups, M. Prietula, K. Carley & L. Gasser (Eds), Menlo Park CA: AAAI/MIT Press, pp. 131-152, 1998.
  27. Ontology Development 101: A Guide to Creating Your First Ontology Natalya F. Noy and Deborah L. McGuinness Stanford University, Stanford, CA, 94305
  28. A Practical Guide To Building OWL Ontologies Using Protege 4 and CO-ODE Tools Edition 1.3 – The University Of Manchester - March 24, 2011.
  29. Building an effective Semantic Web for Health Care and the Life Sciences - Michel Dumontier Department of Biology, Institute of Biochemistry, School of Computer Science, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario, Canada, K1S5B6 2007.

  • Abraham Silberschatz, A., Henry F. Korth, and S. Sudarshan. "Ontology (information science)." JSON 195 XML 204 Web Ontology Language 216 Resource Description Framework 226: 16.
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  • Steele, Louis. Knowledge Management 214 Success Secrets-214 Most Asked Questions On Knowledge Management-What You Need To Know. Emereo Publishing, 2014.