Advertisement

Triggering Ontology Alignment Revalidation Based on the Degree of Change Significance on the Ontology Concept Level

  • Adrianna Kozierkiewicz
  • Marcin PietranikEmail author
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 353)

Abstract

Following a common definition, ontologies can be seen as a formal specification of a conceptualisation. However, it cannot be expected that there will be no changes applied to them. Obviously, any application build on top of some ontology needs to adjust to the introduced alterations. For example, a mapping designated between two ontologies (also called an ontology alignment) is valid only if participating ontologies are fixed. In this paper we present a function that can indicate, whether or not, the aforementioned alignment needs updating, in order to follow modifications done to participating ontologies, and to avoid mapping them again from scratch.

Keywords

Ontology evolution Ontology alignment Knowledge management Consensus theory 

Notes

Acknowledgement

This research project was supported by grant No. 2017/26/D/ST6/00251 from the National Science Centre, Poland.

References

  1. 1.
    Achichi, M., et al.: Results of the ontology alignment evaluation initiative 2017. In: OM 2017–12th ISWC Workshop on Ontology Matching, pp. 61–113 (2017). No commercial editorGoogle Scholar
  2. 2.
    Allocca, C., d’Aquin, M., Motta, E.: Detecting different versions of ontologies in large ontology repositories. In: Proceedings of IWOD 2009, Washington, D.C., USA (2009)Google Scholar
  3. 3.
    Dinh, D., Dos Reis, J.C., Pruski, C., Da Silveira, M., Reynaud-Delaître, C.: Identifying relevant concept attributes to support mapping maintenance under ontology evolution. Web Semant.: Sci. Serv. Agents World Wide Web 29, 53–66 (2014)CrossRefGoogle Scholar
  4. 4.
    Euzenat, J.: Revision in networks of ontologies. Artif. Intell. 228, 195–216 (2015)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Grandi, F.: Multi-temporal RDF ontology versioning. In: Proceedings of IWOD 2009, Washington, D.C., USA (2009)Google Scholar
  6. 6.
    Hartung, M., Groß, A., Rahm, E.: COnto-Diff: generation of complex evolution mappings for life science ontologies. J. Biomed. Inform. 46(1), 15–32 (2013)CrossRefGoogle Scholar
  7. 7.
    Heflin, J., Pan, Z.: A model theoretic semantics for ontology versioning. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 62–76. Springer, Heidelberg (2004).  https://doi.org/10.1007/978-3-540-30475-3_6CrossRefGoogle Scholar
  8. 8.
    Klein, M., Fensel, D., Kiryakov, A., Ognyanov, D.: Ontology versioning and change detection on the web. In: Gómez-Pérez, A., Benjamins, V.R. (eds.) EKAW 2002. LNCS (LNAI), vol. 2473, pp. 197–212. Springer, Heidelberg (2002).  https://doi.org/10.1007/3-540-45810-7_20CrossRefzbMATHGoogle Scholar
  9. 9.
    Khattak, A.M., Latif, K., Lee, S.: Change management in evolving web ontologies. Knowl.-Based Syst. 37, 1–18 (2013)CrossRefGoogle Scholar
  10. 10.
    Kondylakis, H., Plexousakis, D.: Ontology evolution without tears. J. Web Semant. 19, 42–58 (2013)CrossRefGoogle Scholar
  11. 11.
    Kozierkiewicz, A., Pietranik, M.: The knowledge increase estimation framework for integration of ontology instances’ relations. In: Lupeikiene, A., Vasilecas, O., Dzemyda, G. (eds.) DB&IS 2018. Communications in Computer and Information Science, vol. 838, pp. 172–186. Springer, Cham (2018).  https://doi.org/10.1007/978-3-319-97571-9_15CrossRefGoogle Scholar
  12. 12.
    Jiménez-Ruiz, E., Cuenca Grau, B.: LogMap: logic-based and scalable ontology matching. In: Aroyo, L., et al. (eds.) ISWC 2011. LNCS, vol. 7031, pp. 273–288. Springer, Heidelberg (2011).  https://doi.org/10.1007/978-3-642-25073-6_18CrossRefGoogle Scholar
  13. 13.
    Papavassiliou, V., Flouris, G., Fundulaki, I., Kotzinos, D., Christophides, V.: High-level change detection in RDF(S) KBs. ACM Trans. Database Syst. 38(1), 1–42 (2013)MathSciNetGoogle Scholar
  14. 14.
    Pietranik, M., Nguyen, N.T.: A Multi-atrribute based framework for ontology aligning. Neurocomputing 146, 276–290 (2014).  https://doi.org/10.1016/j.neucom.2014.03.067CrossRefGoogle Scholar
  15. 15.
    Pietranik, M., Nguyen, N.T.: Framework for ontology evolution based on a multi-attribute alignment method. In: CYBCONF 2015, pp. 108–112 (2015).  https://doi.org/10.1109/CYBConf.2015.7175915
  16. 16.
    Sassi, N., Jaziri, W., Gargouri, F.: Z-based formalization of kits of changes to maintain ontology consistency. In: Proceedings of KEOD 2009, pp. 388–391 (2009)Google Scholar
  17. 17.
    Zablith, F., et al.: Ontology evolution: a process-centric survey. Knowl. Eng. Rev. 30(1), 45–75 (2015)CrossRefGoogle Scholar
  18. 18.
    Zekri, A., Brahmia, Z., Grandi, F., Bouaziz, R.: \(\tau \)OWL: a systematic approach to temporal versioning of semantic web ontologies. J. Data Semant. 5(3), 141–163 (2016)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Faculty of Computer Science and ManagementWroclaw University of Science and TechnologyWroclawPoland

Personalised recommendations