Medical Ontology Validation through Question Answering

  • Asma Ben Abacha
  • Marcos Da Silveira
  • Cédric Pruski
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7885)


Medical ontology construction is an interactive process that requires the collaboration of both ICT and medical experts. The complexity of the medical domain and the formal description languages makes this collaboration a time consuming and error-prone task. In this paper, we define an ontology validation method that hides the complexity of the formal description languages behind a question-answering game. The proposed approach differs from ”classic” logical-consistency validation approaches and tackles the validation of the domain conceptualization. Reasoning techniques and verbalization methods are used to transform statements inferred from ontologies into natural language questions. The answers of the domain experts to these questions are used to validate and improve the ontology by identifying where it needs to be modified. The validation system then performs automatically the ontology updates needed to correct the detected errors.


Ontology Validation Natural Language Processing Question Generation Medical Domain RDFS OWL 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Liu, K., Hogan, W.R., Crowley, R.S.: Natural language processing methods and systems for biomedical ontology learning. Journal of Biomedical Informatics 44(1), 163–179 (2011)CrossRefGoogle Scholar
  2. 2.
    Navigli, R., Velardi, P.: From glossaries to ontologies: Extracting semantic structure from textual definitions. In: Proceedings of the 2008 Conference on Ontology Learning and Population: Bridging the Gap between Text and Knowledge, pp. 71–87. IOS Press, Amsterdam (2008)Google Scholar
  3. 3.
    Ruiz-Martínez, J.M., Valencia-García, R., Fernández-Breis, J.T., Sánchez, F.G., Martínez-Béjar, R.: Ontology learning from biomedical natural language documents using umls. Expert Systems with Applications 38(10), 12365–12378 (2011)CrossRefGoogle Scholar
  4. 4.
    vor der Bruck, T., Stenzhorn, H.: Logical Ontology Validation Using an Automatic Theorem Prover. In: Proceedings of the 2010 Conference on ECAI 2010: 19th European Conference on Artificial Intelligence, pp. 491–496. IOS Press (2010)Google Scholar
  5. 5.
    Poveda-Villalón, M., Suárez-Figueroa, M.C., Gómez-Pérez, A.: Validating Ontologies with OOPS! In: ten Teije, A., Völker, J., Handschuh, S., Stuckenschmidt, H., d’Acquin, M., Nikolov, A., Aussenac-Gilles, N., Hernandez, N. (eds.) EKAW 2012. LNCS, vol. 7603, pp. 267–281. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  6. 6.
    Pohl, M., Wiltner, S., Rind, A., Aigner, W., Miksch, S., Turic, T., Drexler, F.: Patient development at a glance: An evaluation of a medical data visualization. In: Campos, P., Graham, N., Jorge, J., Nunes, N., Palanque, P., Winckler, M. (eds.) INTERACT 2011, Part IV. LNCS, vol. 6949, pp. 292–299. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  7. 7.
    Pammer, V.: Automatic Support for Ontology Evaluation Review of Entailed Statements and Assertional Effects for OWL Ontologies. PhD thesis, Graz University of Technology (March 2010)Google Scholar
  8. 8.
    Gangemi, A., Catenacci, C., Ciaramita, M., Lehmann, J.: Modelling Ontology Evaluation and Validation. In: Sure, Y., Domingue, J. (eds.) ESWC 2006. LNCS, vol. 4011, pp. 140–154. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  9. 9.
    Gruber, T.: Ontology. In: Encyclopedia of Database Systems (2008)Google Scholar
  10. 10.
    Gómez-Pérez, A.: Ontology evaluation. In: Handbook on Ontologies, pp. 251–274 (2004)Google Scholar
  11. 11.
    Engelbrecht, R.: Expert systems for medicine—functions and developments. Zentralbl Gynakol 119(9), 428–434 (1997)Google Scholar
  12. 12.
    Hotvedt, M.O.: Continuing medical education: actually learning rather than simply listening. JAMA 275(21), 1637–1638 (1996)CrossRefGoogle Scholar
  13. 13.
    Porzel, R., Malaka, R.: A Task-based Approach for Ontology Evaluation. In: Procceding of ECAI 2004, Workshop Ontology Learning and Population, Valencia, Spain (August 2004)Google Scholar
  14. 14.
    Gruber, T.R.: A translation approach to portable ontology specifications. Knowledge Acquisition 5(2), 199–220 (1993)CrossRefGoogle Scholar
  15. 15.
    Hearst, M.: Automatic acquisition of hyponyms from large text corpora. In: Proceedings of the 14th International Conference on Computational Linguistics (COLING 1992), pp. 539–545 (1992)Google Scholar
  16. 16.
    Khoo, C.S., Na, J.C., Wang, V.W., Chan, S.: Developing an ontology for encoding disease treatment information in medical abstracts. DESIDOC Journal of Library & Information Technology 31(2) (2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Asma Ben Abacha
    • 1
  • Marcos Da Silveira
    • 1
  • Cédric Pruski
    • 1
  1. 1.Ressource Centre for Health Care Technologies (CR SANTEC)Public Research Centre Henri TudorEsch-sur-AlzetteLuxembourg

Personalised recommendations