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Pitfalls in Ontologies and TIPS to Prevent Them

  • C. Maria KeetEmail author
  • Mari Carmen Suárez-Figueroa
  • María Poveda-Villalón
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 454)

Abstract

A growing number of ontologies are already available thanks to development initiatives in many different fields. In such ontology developments, developers must tackle a wide range of difficulties and handicaps, which can result in the appearance of anomalies in the resulting ontologies. Therefore, ontology evaluation plays a key role in ontology development. OOPS! is an on-line tool that automatically detects pitfalls, considered as potential errors or problems—and thus may help ontology developers to improve their ontologies. To gain insight in the existence of pitfalls and to assess whether there are differences among ontologies developed by novices, a random set of already scanned ontologies, and existing well-known ones, data of 406 OWL ontologies were analysed on OOPS!’s 21 pitfalls, of which 24 ontologies were also examined manually on the detected pitfalls. The various analyses performed show only minor differences between the three sets of ontologies, therewith providing a general landscape of pitfalls in ontologies. We also propose guidelines to avoid the inclusion of such common pitfalls in new ontologies, the Typical pItfalls Prevention Scheme (TIPS), so as to increase the baseline quality of OWL ontologies.

Notes

Acknowledgements

This work has been partially supported by the Spanish projects BabelData (TIN2010-17550) and BuscaMedia (CENIT 2009-1026).

References

  1. 1.
    Noy, N., McGuinness, D.: Ontology Development 101: A guide to creating your first ontology. Number KSL-01-05, and Stanford Medical Informatics Technical Report SMI-2001-0880, March 2001Google Scholar
  2. 2.
    Rector, A., Drummond, N., Horridge, M., Rogers, J., Knublauch, H., Stevens, R., Wang, H., Wroe, C.: OWL pizzas: practical experience of teaching OWL-DL: common errors & common patterns. In: Motta, E., Shadbolt, N.R., Stutt, A., Gibbins, N. (eds.) EKAW 2004. LNCS, vol. 3257, pp. 63–81. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  3. 3.
    Roussey, C., Corcho, O., Vilches-Blázquez, L.: A catalogue of OWL ontology antipatterns. In: Proceedings of K-CAP 2009, pp. 205–206 (2009)Google Scholar
  4. 4.
    Poveda, M., Suárez-Figueroa, M.C., Gómez-Pérez, A.: Common pitfalls in ontology development. In: Meseguer, P., Mandow, L., Gasca, R.M. (eds.) CAEPIA 2009. LNCS, vol. 5988, pp. 91–100. Springer, Heidelberg (2010) CrossRefGoogle 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.
    Keet, C.M.: Detecting and revising flaws in OWL object property expressions. 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. 252–266. Springer, Heidelberg (2012) CrossRefGoogle Scholar
  7. 7.
    Guarino, N., Welty, C.: An overview of ontoclean. In: Staab, S., Studer, R. (eds.) Handbook on Ontologies, pp. 201–220. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  8. 8.
    Vrandečić, D.: Ontology evaluation. In: Staab, S., Studer, R. (eds.) Handbook on Ontologies, 2nd edn, pp. 293–313. Springer, Heidelberg (2009)Google Scholar
  9. 9.
    Gómez-Pérez, A.: Ontology evaluation. In: Staab, S., Studer, R. (eds.) Handbook on Ontologies. International Handbooks on Information Systems, pp. 251–274. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  10. 10.
    Poveda-Villalón, M., Suárez-Figueroa, M.C., Gómez-Pérez, A.: A double classification of common pitfalls in ontologies. In: Proceedings of Workshop on Ontology Quality (OntoQual 2010). CEUR-WS (2010) C-located with EKAW 2010Google Scholar
  11. 11.
    Guarino, N., Oberle, D., Staab, S.: What is an ontology? In: Staab, S., Studer, R. (eds.) Handbook on Ontologies, pp. 1–17. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  12. 12.
    Brank, J., Grobelnik, M., Mladenic, D.: A survey of ontology evaluation techniques. In: Proceedings of SiKDD 2005, Ljubljana, Slovenia (2005)Google Scholar
  13. 13.
    Sabou, M., Fernandez, M.: Ontology (network) evaluation. In: Suárez-Figueroa, M.C., Gómez-Pérez, A., Motta, E., Gangemi, A. (eds.) Ontology Engineering in a Networked World, pp. 193–212. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  14. 14.
    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
  15. 15.
    Poveda-Villalón, M., Vatant, B., Suárez-Figueroa, M.C., Gomez-Perez, A.: Detecting good practices and pitfalls when publishing vocabularies on the web, Sydney, Australia, 21 October 2013Google Scholar
  16. 16.
    Suominen, O., Mader, C.: Assessing and improving the quality of SKOS vocabularies. J. Data Semant. 2(2), 1–27 (2013)Google Scholar
  17. 17.
    Schulz, S., Stenzhorn, H., Boekers, M., Smith, B.: Strengths and limitations of formal ontologies in the biomedical domain. Electron. J. Commun. Info. Innov. Health (Special Issue on Ontologies, Semantic Web and Health) 3(1), 31–45 (2009)Google Scholar
  18. 18.
    Keet, C.M.: The use of foundational ontologies in ontology development: an empirical assessment. In: Antoniou, G., Grobelnik, M., Simperl, E., Parsia, B., Plexousakis, D., De Leenheer, P., Pan, J. (eds.) ESWC 2011, Part I. LNCS, vol. 6643, pp. 321–335. Springer, Heidelberg (2011) CrossRefGoogle Scholar
  19. 19.
    Aguado de Cea, G., Gómez-Pérez, A., Montiel-Ponsoda, E., Suárez-Figueroa, M.C.: Natural language-based approach for helping in the reuse of ontology design patterns. In: Gangemi, A., Euzenat, J. (eds.) EKAW 2008. LNCS (LNAI), vol. 5268, pp. 32–47. Springer, Heidelberg (2008) CrossRefGoogle Scholar
  20. 20.
    Keet, C.M., Fernández-Reyes, F.C., Morales-González, A.: Representing mereotopological relations in OWL ontologies with OntoPartS. In: Simperl, E., Cimiano, P., Polleres, A., Corcho, O., Presutti, V. (eds.) ESWC 2012. LNCS, vol. 7295, pp. 240–254. Springer, Heidelberg (2012) CrossRefGoogle Scholar
  21. 21.
    Curé, O., Prié, Y., Champin, P.-A.: A knowledge-based approach to augment applications with interaction traces. 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. 317–326. Springer, Heidelberg (2012) CrossRefGoogle Scholar
  22. 22.
    Braga, B.F.B., Almeida, J.P.A., Guizzardi, G., Benevides, A.B.: Transforming ontoUML into alloy: towards conceptual model validation using a lightweight formal methods. Innov. Syst. Softw. Eng. 6(1–2), 55–63 (2010)CrossRefGoogle Scholar
  23. 23.
    Halpin, T.: Information Modeling and Relational Databases. Morgan Kaufmann Publishers, San Francisco (2001)Google Scholar
  24. 24.
    Keet, C.M.: Transforming semi-structured life science diagrams into meaningful domain ontologies with DiDOn. J. Biomed. Inform. 45, 482–494 (2012)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • C. Maria Keet
    • 1
    Email author
  • Mari Carmen Suárez-Figueroa
    • 2
  • María Poveda-Villalón
    • 2
  1. 1.School of Mathematics, Statistics, and Computer Science, UKZN/CSIR-Meraka Centre for Artificial Intelligence ResearchUniversity of KwaZulu-NatalDurbanSouth Africa
  2. 2.Ontology Engineering Group, Departamento de Inteligencia Artificial, Facultad de InformáticaUniversidad Politécnica de MadridMadridSpain

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