Fast ABox Consistency Checking Using Incomplete Reasoning and Caching

  • Christian Meilicke
  • Daniel RuffinelliEmail author
  • Andreas Nolle
  • Heiko Paulheim
  • Heiner Stuckenschmidt
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10364)


Reasoning with complex ontologies can be a resource-intensive task, which can be an obstacle, e.g., for real-time applications. Hence, weakening the constraints of soundness and/or completeness is often an approach to practical solutions. In this paper, we propose an extension of incomplete reasoning methods for checking the consistency of a large number of ABoxes against a given TBox. In particular, we use and extend the clash queries proposed by Lembo et al. [9] for DL-Lite to compute inconsistent patterns of ABox assertions. By caching instantiations of these patterns, we are able to reduce the amount of reasoning required to determine the inconsistency of an ABox with every previously processed ABox. We present experimental results of our approach in terms of runtime and accuracy and compare it against complete reasoning techniques, the reasoning approach for DL-Lite \(_{\mathcal {A}}\), and an approximate reasoning approach based on machine learning proposed in [15].


ABox Assertions Type Clash DBpedia Single ABox Inconsistent Combinations 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Baader, F.: The Description Logic Handbook: Theory, Implementation, and Applications. Cambridge University Press, Cambridge (2003)zbMATHGoogle Scholar
  2. 2.
    Calvanese, D., De Giacomo, G., Lembo, D., Lenzerini, M., Rosati, R.: Tractable reasoning and efficient query answering in description logics: the DL-Lite family. J. Autom. Reasoning 39(3), 385–429 (2007)MathSciNetCrossRefzbMATHGoogle Scholar
  3. 3.
    Flouris, G., Huang, Z., Pan, J.Z., Plexousakis, D., Wache, H.: Inconsistencies, negations and changes in ontologies. In: Proceedings of the National Conference on Artificial Intelligence, vol. 21, no. 2, p. 1295 (2006)Google Scholar
  4. 4.
    Gangemi, A., Mika, P.: Understanding the semantic web through descriptions and situations. In: Meersman, R., Tari, Z., Schmidt, D.C. (eds.) OTM 2003. LNCS, vol. 2888, pp. 689–706. Springer, Heidelberg (2003). doi: 10.1007/978-3-540-39964-3_44 CrossRefGoogle Scholar
  5. 5.
    Horridge, M., Parsia, B., Sattler, U.: Explaining inconsistencies in OWL ontologies. In: Godo, L., Pugliese, A. (eds.) SUM 2009. LNCS (LNAI), vol. 5785, pp. 124–137. Springer, Heidelberg (2009). doi: 10.1007/978-3-642-04388-8_11 CrossRefGoogle Scholar
  6. 6.
    Horrocks, I., Motik, B., Wang, Z.: The HermiT OWL reasoner. In: Proceedings of the 1st International Workshop on OWL Reasoner Evaluation (ORE-2012), Manchester, UK (2012)Google Scholar
  7. 7.
    Kalyanpur, A., Parsia, B., Horridge, M., Sirin, E.: Finding all justifications of OWL DL entailments. In: Aberer, K., Choi, K.-S., Noy, N., Allemang, D., Lee, K.-I., Nixon, L., Golbeck, J., Mika, P., Maynard, D., Mizoguchi, R., Schreiber, G., Cudré-Mauroux, P. (eds.) ASWC/ISWC -2007. LNCS, vol. 4825, pp. 267–280. Springer, Heidelberg (2007). doi: 10.1007/978-3-540-76298-0_20 CrossRefGoogle Scholar
  8. 8.
    Lehmann, J., Isele, R., Jakob, M., Jentzsch, A., Kontokostas, D., Mendes, P.N., Hellmann, S., Morsey, M., Van Kleef, P., Auer, S., et al.: DBpedia-a large-scale, multilingual knowledge base extracted from wikipedia. Semant. Web 6(2), 167–195 (2015)Google Scholar
  9. 9.
    Lembo, D., Lenzerini, M., Rosati, R., Ruzzi, M., Savo, D.F.: Query rewriting for inconsistent DL-Lite ontologies. In: Rudolph, S., Gutierrez, C. (eds.) RR 2011. LNCS, vol. 6902, pp. 155–169. Springer, Heidelberg (2011). doi: 10.1007/978-3-642-23580-1_12 CrossRefGoogle Scholar
  10. 10.
    Lembo, D., Lenzerini, M., Rosati, R., Ruzzi, M., Savo, D.F.: Inconsistency-tolerant first-order rewritability of DL-Lite with identification and denial assertions. In: Proceedings of the 25th International Workshop on Description Logics (2012)Google Scholar
  11. 11.
    Lösch, U., Bloehdorn, S., Rettinger, A.: Graph kernels for RDF data. In: Simperl, E., Cimiano, P., Polleres, A., Corcho, O., Presutti, V. (eds.) ESWC 2012. LNCS, vol. 7295, pp. 134–148. Springer, Heidelberg (2012). doi: 10.1007/978-3-642-30284-8_16 CrossRefGoogle Scholar
  12. 12.
    Nickel, M., Murphy, K., Tresp, V., Gabrilovich, E.: A review of relational machine learning for knowledge graphs. Proc. IEEE 104(1), 11–33 (2016). CrossRefGoogle Scholar
  13. 13.
    Nolle, A., Meilicke, C., Chekol, M., Nemirovski, G., Stuckenschmidt, H.: Schema-based debugging of federated data sources. In: Proceedings of the 22nd European Conference on Artificial Intelligence (ECAI2016). IOS Press (2016)Google Scholar
  14. 14.
    Paulheim, H., Gangemi, A.: Serving DBpedia with DOLCE – more than just adding a cherry on top. In: Arenas, M., et al. (eds.) ISWC 2015. LNCS, vol. 9366, pp. 180–196. Springer, Cham (2015). doi: 10.1007/978-3-319-25007-6_11 CrossRefGoogle Scholar
  15. 15.
    Paulheim, H., Stuckenschmidt, H.: Fast approximate A-Box consistency checking using machine learning. In: Sack, H., Blomqvist, E., d’Aquin, M., Ghidini, C., Ponzetto, S.P., Lange, C. (eds.) ESWC 2016. LNCS, vol. 9678, pp. 135–150. Springer, Cham (2016). doi: 10.1007/978-3-319-34129-3_9 CrossRefGoogle Scholar
  16. 16.
    Poggi, A., Lembo, D., Calvanese, D., Giacomo, G., Lenzerini, M., Rosati, R.: Linking data to ontologies. In: Spaccapietra, S. (ed.) Journal on Data Semantics X. LNCS, vol. 4900, pp. 133–173. Springer, Heidelberg (2008). doi: 10.1007/978-3-540-77688-8_5 CrossRefGoogle Scholar
  17. 17.
    Steigmiller, A., Liebig, T., Glimm, B.: Konclude: system description. J. Web Sem. 27, 78–85 (2014). CrossRefzbMATHGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Christian Meilicke
    • 1
  • Daniel Ruffinelli
    • 1
    Email author
  • Andreas Nolle
    • 2
  • Heiko Paulheim
    • 1
  • Heiner Stuckenschmidt
    • 1
  1. 1.Research Group Data and Web ScienceUniversity of MannheimMannheimGermany
  2. 2.Data Science, Department of Business and Computer ScienceAlbstadt-Sigmaringen UniversityAlbstadtGermany

Personalised recommendations