Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content
SpringerLink
Log in

Repairing \(\mathcal{{EL}}\) Ontologies Using Weakening and Completing

  • Conference paper
  • First Online:
The Semantic Web (ESWC 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13870))

Included in the following conference series:

Abstract

The quality of ontologies in terms of their correctness and completeness is crucial for developing high-quality ontology-based applications. Traditional debugging techniques repair ontologies by removing unwanted axioms, but may thereby remove consequences that are correct in the domain of the ontology. In this paper we propose an interactive approach to mitigate this for \(\mathcal{{EL}}\) ontologies by axiom weakening and completing. We present the first approach for repairing that takes into account removing, weakening and completing. We show different combination strategies, discuss the influence on the final ontologies and show experimental results. We show that previous work has only considered special cases and that there is a trade-off, and how to deal with it, involving the amount of validation work for a domain expert and the quality of the ontology in terms of correctness and completeness. We also present new algorithms for weakening and completing.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    This term has been used with different meanings. In this paper we refer to completing as the dual task of weakening. The term has been used with other meanings in, e.g., [4, 31]. Related terms are, e.g., ontology extension [21], ontology learning [6], ontology enrichment [11], and ontology revision [24].

  2. 2.

    As we do not deal with individuals in this paper, we do not use individuals in the later sections.

  3. 3.

    We do not take up consistency of TBoxes, i.e., whether a model exists or not, in this paper as every \(\mathcal{{EL}}\) TBox is consistent.

  4. 4.

    We note that in this paper we deal with removing and not the full debugging problem, i.e., we assume that the axioms to be removed are already found. Removing can be seen as a simple kind of debugging, or as the second step of the debugging process.

  5. 5.

    Weaker limitations are possible, but the weaker the restriction, the larger the solution search space and the higher the probability of a less usable practical system.

References

  1. Arif, M.F., Mencía, C., Ignatiev, A., Manthey, N., Peñaloza, R., Marques-Silva, J.: BEACON: an efficient SAT-based tool for debugging \({\cal{EL}}{^+}\) ontologies. In: Creignou, N., Le Berre, D. (eds.) SAT 2016. LNCS, vol. 9710, pp. 521–530. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-40970-2_32

    Chapter  MATH  Google Scholar 

  2. Baader, F., Brandt, S., Lutz, C.: Pushing the \({\cal{E} L}\) envelope. In: IJCAI 2005: Proceedings of the 19th International Joint Conference on Artificial Intelligence, pp. 364–369 (2005)

    Google Scholar 

  3. Baader, F., Calvanese, D., McGuinness, D.L., Nardi, D., Patel-Schneider, P.F. (eds.): The Description Logic Handbook: Theory, Implementation, and Applications. Cambridge University Press, Cambridge (2003)

    Google Scholar 

  4. Baader, F., Ganter, B., Sertkaya, B., Sattler, U.: Completing description logic knowledge bases using formal concept analysis. In: IJCAI 2007: Proceedings of the 20th International Joint Conference on Artificial Intelligence, pp. 230–235 (2007)

    Google Scholar 

  5. Baader, F., Kriegel, F., Nuradiansyah, A., Peñaloza, R.: Making repairs in description logics more gentle. In: KR 2018: 16th International Conference on Principles of Knowledge Representation and Reasoning, pp. 319–328 (2018)

    Google Scholar 

  6. Buitelaar, P., Cimiano, P., Magnini, B.: Ontology Learning from Text: Methods, Evaluation and Applications. IOS Press (2005)

    Google Scholar 

  7. Confalonieri, R., Galliani, P., Kutz, O., Porello, D., Righetti, G., Troquard, N.: Towards even more irresistible axiom weakening. In: Proceedings of the 33rd International Workshop on Description Logics. CEUR, vol. 2663 (2020)

    Google Scholar 

  8. Dragisic, Z., Ivanova, V., Li, H., Lambrix, P.: Experiences from the anatomy track in the ontology alignment evaluation initiative. J. Biomed. Semant. 8(1), 56:1–56:28 (2017). https://doi.org/10.1186/s13326-017-0166-5

  9. Du, J., Qi, G., Fu, X.: A practical fine-grained approach to resolving incoherent OWL 2 DL terminologies. In: CIKM 2014: Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, pp. 919–928 (2014). https://doi.org/10.1145/2661829.2662046

  10. Du, J., Wan, H., Ma, H.: Practical TBox abduction based on justification patterns. In: Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI 2017), pp. 1100–1106 (2017)

    Google Scholar 

  11. Ferré, S., Rudolph, S.: Advocatus Diaboli – exploratory enrichment of ontologies with negative constraints. In: ten Teije, A., et al. (eds.) EKAW 2012. LNCS (LNAI), vol. 7603, pp. 42–56. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-33876-2_7

    Chapter  Google Scholar 

  12. Fleischhacker, D., Meilicke, C., Völker, J., Niepert, M.: Computing incoherence explanations for learned ontologies. In: Faber, W., Lembo, D. (eds.) RR 2013. LNCS, vol. 7994, pp. 80–94. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-39666-3_7

    Chapter  Google Scholar 

  13. Ji, Q., Gao, Z., Huang, Z., Zhu, M.: An efficient approach to debugging ontologies based on patterns. In: Pan, J.Z., et al. (eds.) JIST 2011. LNCS, vol. 7185, pp. 425–433. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-29923-0_33

    Chapter  Google Scholar 

  14. Kalyanpur, A., Parsia, B., Horridge, M., Sirin, E.: Finding all justifications of OWL DL entailments. In: Aberer, K., et al. (eds.) ASWC/ISWC -2007. LNCS, vol. 4825, pp. 267–280. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-76298-0_20

    Chapter  Google Scholar 

  15. Kalyanpur, A., Parsia, B., Sirin, E., Cuenca-Grau, B.: Repairing unsatisfiable concepts in OWL ontologies. In: Sure, Y., Domingue, J. (eds.) ESWC 2006. LNCS, vol. 4011, pp. 170–184. Springer, Heidelberg (2006). https://doi.org/10.1007/11762256_15

    Chapter  Google Scholar 

  16. Kalyanpur, A., Parsia, B., Sirin, E., Hendler, J.: Debugging unsatisfiable classes in OWL ontologies. J. Web Semant. 3(4), 268–293 (2005). https://doi.org/10.1016/j.websem.2005.09.005

    Article  Google Scholar 

  17. Lam, J.S.C., Sleeman, D.H., Pan, J.Z., Vasconcelos, W.W.: A fine-grained approach to resolving unsatisfiable ontologies. J. Data Semant. 10, 62–95 (2008). https://doi.org/10.1007/978-3-540-77688-8_3

    Article  MATH  Google Scholar 

  18. Lambrix, P., Dragisic, Z., Ivanova, V.: Get my pizza right: repairing missing is-a relations in ALC ontologies. In: Takeda, H., Qu, Y., Mizoguchi, R., Kitamura, Y. (eds.) JIST 2012. LNCS, vol. 7774, pp. 17–32. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-37996-3_2

    Chapter  Google Scholar 

  19. Lambrix, P., Wei-Kleiner, F., Dragisic, Z.: Completing the is-a structure in light-weight ontologies. J. Biomed. Semant. 6 (2015). https://doi.org/10.1186/s13326-015-0002-8

  20. Lehmann, J., Bühmann, L.: ORE - a tool for repairing and enriching knowledge bases. In: Patel-Schneider, P.F., et al. (eds.) ISWC 2010. LNCS, vol. 6497, pp. 177–193. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-17749-1_12

    Chapter  Google Scholar 

  21. Li, H., Armiento, R., Lambrix, P.: A method for extending ontologies with application to the materials science domain. Data Sci. J. 18(1) (2019). https://doi.org/10.5334/dsj-2019-050

  22. Meyer, T., Lee, K., Booth, R., Pan, J.: Finding maximally satisfiable terminologies for the description logic ALC. In: Proceedings, The Twenty-First National Conference on Artificial Intelligence and the Eighteenth Innovative Applications of Artificial Intelligence Conference (AAAI 2006), pp. 269–274 (2006)

    Google Scholar 

  23. Moodley, K., Meyer, T., Varzinczak, I.J.: Root justifications for ontology repair. In: Rudolph, S., Gutierrez, C. (eds.) RR 2011. LNCS, vol. 6902, pp. 275–280. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-23580-1_24

    Chapter  Google Scholar 

  24. Nikitina, N., Rudolph, S., Glimm, B.: Interactive ontology revision. J. Web Semant. 12–13, 118–130 (2012). https://doi.org/10.1016/j.websem.2011.12.002

    Article  Google Scholar 

  25. Pesquita, C., Faria, D., Santos, E., Couto, F.M.: To repair or not to repair: reconciling correctness and coherence in ontology reference alignments. In: Proceedings of the 8th International Workshop on Ontology Matching. CEUR, vol. 1111, pp. 13–24 (2013)

    Google Scholar 

  26. Rodler, P., Schmid, W.: On the impact and proper use of heuristics in test-driven ontology debugging. In: Benzmüller, C., Ricca, F., Parent, X., Roman, D. (eds.) RuleML+RR 2018. LNCS, vol. 11092, pp. 164–184. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-99906-7_11

    Chapter  MATH  Google Scholar 

  27. Schekotihin, K., Rodler, P., Schmid, W.: OntoDebug: interactive ontology debugging plug-in for Protégé. In: Ferrarotti, F., Woltran, S. (eds.) FoIKS 2018. LNCS, vol. 10833, pp. 340–359. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-90050-6_19

    Chapter  Google Scholar 

  28. Schlobach, S.: Debugging and semantic clarification by pinpointing. In: Gómez-Pérez, A., Euzenat, J. (eds.) ESWC 2005. LNCS, vol. 3532, pp. 226–240. Springer, Heidelberg (2005). https://doi.org/10.1007/11431053_16

    Chapter  Google Scholar 

  29. Schlobach, S., Cornet, R.: Non-standard reasoning services for the debugging of description logic terminologies. In: IJCAI, pp. 355–360 (2003)

    Google Scholar 

  30. Schlobach, S., Huang, Z., Cornet, R., van Harmelen, F.: Debugging incoherent terminologies. J. Autom. Reason. 39(3), 317–349 (2007). https://doi.org/10.1007/s10817-007-9076-z

    Article  MathSciNet  MATH  Google Scholar 

  31. Sertkaya, B.: OntoComP: a Protégé plugin for completing OWL ontologies. In: Aroyo, L., et al. (eds.) ESWC 2009. LNCS, vol. 5554, pp. 898–902. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-02121-3_78

    Chapter  Google Scholar 

  32. Shchekotykhin, K.M., Friedrich, G., Fleiss, P., Rodler, P.: Interactive ontology debugging: two query strategies for efficient fault localization. J. Web Semant. 12, 88–103 (2012). https://doi.org/10.1016/j.websem.2011.12.006

    Article  Google Scholar 

  33. Troquard, N., Confalonieri, R., Galliani, P., Peñaloza, R., Porello, D., Kutz, O.: Repairing ontologies via axiom weakening. In: Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018), pp. 1981–1988 (2018). https://doi.org/10.1609/aaai.v32i1.11567

  34. Wang, K., Wang, Z., Topor, R., Pan, J.Z., Antoniou, G.: Concept and role forgetting in \({\cal{ALC}}\) ontologies. In: Bernstein, A., et al. (eds.) ISWC 2009. LNCS, vol. 5823, pp. 666–681. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-04930-9_42

    Chapter  Google Scholar 

  35. Wei-Kleiner, F., Dragisic, Z., Lambrix, P.: Abduction framework for repairing incomplete \(\cal{EL} \) ontologies: complexity results and algorithms. In: Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI 2014), pp. 1120–1127 (2014). https://doi.org/10.1609/aaai.v28i1.8858

Download references

Acknowledgement

We thank Olaf Hartig for discussions leading to the Hasse diagrams. This work is financially supported by the Swedish e-Science Research Centre (SeRC) and the Swedish Research Council (Vetenskapsrådet, dnr 2018-04147).

Author information

Authors and Affiliations

  1. Linköping University, Linköping, Sweden

    Ying Li & Patrick Lambrix

  2. The Swedish e-Science Research Centre, Linköping, Sweden

    Ying Li & Patrick Lambrix

  3. University of Gävle, Gävle, Sweden

    Patrick Lambrix

Authors
  1. Ying Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Patrick Lambrix
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Patrick Lambrix .

Editor information

Editors and Affiliations

  1. Universidade de Lisboa, Lisbon, Portugal

    Catia Pesquita

  2. University of London, London, UK

    Ernesto Jimenez-Ruiz

  3. Rensselaer Polytechnic Institute, Troy, MI, USA

    Jamie McCusker

  4. Universidade de Lisboa, Lisbon, Portugal

    Daniel Faria

  5. Fondazione Bruno Kessler, Povo, Trento, Italy

    Mauro Dragoni

  6. KU Leuven, Sint-Katelijne-Waver, Belgium

    Anastasia Dimou

  7. EURECOM, Biot, France

    Raphael Troncy

  8. University of Mannheim, Mannheim, Germany

    Sven Hertling

1 Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (pdf 179 KB)

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Li, Y., Lambrix, P. (2023). Repairing \(\mathcal{{EL}}\) Ontologies Using Weakening and Completing. In: Pesquita, C., et al. The Semantic Web. ESWC 2023. Lecture Notes in Computer Science, vol 13870. Springer, Cham. https://doi.org/10.1007/978-3-031-33455-9_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-33455-9_18

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-33454-2

  • Online ISBN: 978-3-031-33455-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation