Abstract
The ontology-based data access (OBDA) paradigm can ease access to heterogeneous and incomplete data sources in many application domains. However, state-of-the-art tools are still based on the DL-Lite family of description logics (DLs) that underlies OWL 2 QL, which despite its usefulness is not sufficiently expressive for many domains. Accommodating more expressive ontology languages remains an open challenge, and the consensus is that Horn DLs like Horn-\(\mathcal {SHIQ}\) are particularly promising. Query answering in Horn-\(\mathcal {SHIQ}\), a prerequisite for OBDA, is supported in existing reasoners, but many ontologies cannot be handled. This is largely because algorithms build on an ABox-independent approach to ontological reasoning that easily incurs in an exponential behaviour. As an alternative to full ABox-independence, in this paper we advocate taking into account general information about the structure of the ABoxes of interest. This is especially natural in the setting of OBDA, where ABoxes are generated via mappings, and thus have a predictable structure. We present a simple yet effective approach that guides ontological reasoning using the possible combinations of concepts that may occur in the ABox, which can be obtained from the mappings of an OBDA specification. We implemented and tested our optimization in the Clipper reasoner with encouraging results.
This work was supported by the Austrian Science Fund (FWF) projects P30360, P30873, W1255 and by the Free University of Bozen-Bolzano projects STyLoLa, OBATS and QUADRO.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Baader, F., Bienvenu, M., Lutz, C., Wolter, F.: Query and predicate emptiness in ontology-based data access. J. Artif. Intell. Res. 56, 1–59 (2016)
Baader, F., Calvanese, D., McGuinness, D., Nardi, D., Patel-Schneider, P. (eds.): The Description Logic Handbook: Theory, Implementation, and Applications, 2nd edn. Cambridge University Press, Cambridge (2007)
Bienvenu, M., Ortiz, M.: Ontology-mediated query answering with data-tractable description logics. In: Faber, W., Paschke, A. (eds.) Reasoning Web 2015. LNCS, vol. 9203, pp. 218–307. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-21768-0_9
Botoeva, E., Calvanese, D., Santarelli, V., Savo, D.F., Solimando, A., Xiao, G.: Beyond OWL 2 QL in OBDA: rewritings and approximations. In: Proceedings of of AAAI, pp. 921–928. AAAI Press (2016)
Botoeva, E., Kontchakov, R., Ryzhikov, V., Wolter, F., Zakharyaschev, M.: Games for query inseparability of description logic knowledge bases. Artif. Intell. 234, 78–119 (2016)
Botoeva, E., Lutz, C., Ryzhikov, V., Wolter, F., Zakharyaschev, M.: Query inseparability for ALC ontologies. CoRR abs/1902.00014 (2019)
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. Reas. 39(3), 385–429 (2007)
Carral, D., Dragoste, I., Krötzsch, M.: The combined approach to query answering in Horn-ALCHOIQ. In: Proceedings of KR, pp. 339–348. AAAI Press (2018)
Carral, D., González, L., Koopmann, P.: From Horn-SRIQ to datalog: a data-independent transformation that preserves assertion entailment. In: Proceedings of AAAI. AAAI Press (2019)
Das, S., Sundara, S., Cyganiak, R.: R2RML: RDB to RDF mapping language. In: W3C Recommendation, W3C (2012)
Eiter, T., Ortiz, M., Simkus, M., Tran, T., Xiao, G.: Query rewriting for Horn-SHIQ plus rules. In: Proceedings of AAAI, pp. 726–733. AAAI Press (2012)
Hovland, D., Kontchakov, R., Skjæveland, M.G., Waaler, A., Zakharyaschev, M.: Ontology-based data access to Slegge. In: d’Amato, C., et al. (eds.) ISWC 2017. LNCS, vol. 10588, pp. 120–129. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-68204-4_12
Kazakov, Y.: Consequence-driven reasoning for Horn SHIQ ontologies. In: Proceedings of IJCAI, pp. 2040–2045 (2009)
Krötzsch, M., Rudolph, S., Hitzler, P.: Complexity boundaries for Horn description logics. In: Proceedings of AAAI, pp. 452–457. AAAI Press (2007)
Lanti, D., Rezk, M., Xiao, G., Calvanese, D.: The NPD benchmark: reality check for OBDA systems. In: Proceedings of EDBT. ACM Press (2015)
Leone, N., Manna, M., Terracina, G., Veltri, P.: Fast query answering over existential rules. ACM Trans. Comput. Log. 20(2), 1–48 (2019). https://doi.org/10.1145/3308448
Lutz, C., Walther, D., Wolter, F.: Conservative extensions in expressive description logics. In: Proceedings of IJCAI, pp. 453–458 (2007)
Poggi, A., Lembo, D., Calvanese, D., De Giacomo, G., Lenzerini, M., Rosati, R.: Linking data to ontologies. J. Data Semant. 10, 133–173 (2008)
Ren, Y., Pan, J.Z., Zhao, Y.: Soundness preserving approximation for TBox reasoning. In: Proceedings of AAAI, pp. 351–356. AAAI Press (2010)
Rodriguez-Muro, M., Rezk, M.: Efficient SPARQL-to-SQL with R2RML mappings. J. Web Semant. 33, 141–169 (2015)
Shi, L., Cai, X.: An exact fast algorithm for minimum hitting set. In: Third International Joint Conference on Computational Science and Optimization, vol. 1, pp. 64–67 (2010)
Xiao, G., et al.: Ontology-based data access: a survey. In: Proceedings of IJCAI, pp. 5511–5519 (2018)
Xiao, G., Ding, L., Cogrel, B., Calvanese, D.: Virtual knowledge graphs: an overview of systems and use cases. Data Intell. 1, 201–223 (2019)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Bajraktari, L., Ortiz, M., Xiao, G. (2019). Optimizing Horn-\(\mathcal {SHIQ}\) Reasoning for OBDA. In: Ghidini, C., et al. The Semantic Web – ISWC 2019. ISWC 2019. Lecture Notes in Computer Science(), vol 11778. Springer, Cham. https://doi.org/10.1007/978-3-030-30793-6_5
Download citation
DOI: https://doi.org/10.1007/978-3-030-30793-6_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-30792-9
Online ISBN: 978-3-030-30793-6
eBook Packages: Computer ScienceComputer Science (R0)
