Abstract
Constraints have traditionally been used to ensure data quality. Recently, several constraint languages such as SHACL, as well as mechanisms for constraint validation, have been proposed for Knowledge Graphs (KGs). KGs are often enhanced with ontologies that define relevant background knowledge in a formal language such as OWL 2 QL. However, existing systems for constraint validation either ignore these ontologies, or compile ontologies and constraints into rules that should be executed by some rule engine. In the latter case, one has to rely on different systems when validating constrains over KGs and over ontology-enhanced KGs. In this work, we address this problem by defining rewriting techniques that allow to compile an OWL 2 QL ontology and a set of SHACL constraints into another set of SHACL constraints. We show that in the general case the rewriting may not exists, but it always exists for the positive fragment of SHACL. Our rewriting techniques allow to validate constraints over KGs with and without ontologies using the same SHACL validation engines.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
- 2.
- 3.
- 4.
- 5.
Recall that for query rewriting the input is a query q and ontology \(\mathcal {O}\) and the output is another query \(q'\) such that for any database D so-called certain answers of q over \(\langle \mathcal {O}, \mathcal {D} \rangle \) coincide with the answers of \(q'\) over \(\mathcal {D} \) alone [9].
- 6.
The axiom of the kind \(V \sqsubseteq \exists R.C\) in syntactically not in \({\textit{DL-Lite}_R}{}\) but it can be expressed using a “fresh” role \(R_1\) and three axioms: \(V \sqsubseteq \exists R_1\), \(R_1 \sqsubseteq R\) and \(\exists R^{-}_1 \sqsubseteq C\).
- 7.
In this entailment we consider \(\mathcal {M}\) as an infinite conjunction of atoms.
References
Freebase: an open, shared database of the world’s knowledge. freebase.com/
Google KG. google.co.uk/insidesearch/features/search/knowledge.html
W3C: OWL 2 Web Ontology Language. www.w3.org/TR/owl2-overview/
Abiteboul, S., Buneman, P., Suciu, D.: Data on the Web: From Relations to Semistructured Data and XML. Morgan Kaufmann, Burlington (1999)
Abiteboul, S., Hull, R., Vianu, V.: Foundations of Databases. Addison-Wesley, Boston (1995)
Arenas, M., Grau, B.C., Kharlamov, E., Marciuska, S., Zheleznyakov, D.: Faceted search over RDF-based knowledge graphs. J. Web Semant. 37–38, 55–74 (2016)
Arenas, M., Gutiérrez, C., Pérez, J.: Foundations of RDF databases. In: Tessaris, S., et al. (eds.) Reasoning Web 2009. LNCS, vol. 5689, pp. 158–204. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-03754-2_4
Boneva, I., Labra Gayo, J.E., Prud’hommeaux, E.G.: Semantics and validation of shapes schemas for RDF. In: d’Amato, C., et al. (eds.) ISWC 2017. LNCS, vol. 10587, pp. 104–120. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-68288-4_7
Calvanese, D., De Giacomo, G., Lembo, D., Lenzerini, M., Rosati, R.: Tractable reasoning and efficient query answering in description logics: the DL-Lite family. JAR 39, 385–429 (2007)
Calvanese, D., Kharlamov, E., Nutt, W., Zheleznyakov, D.: Evolution of DL – Lite knowledge bases. In: Patel-Schneider, P.F., et al. (eds.) ISWC 2010. LNCS, vol. 6496, pp. 112–128. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-17746-0_8
Cheng, G., Kharlamov, E.: Towards a semantic keyword search over industrial knowledge graphs (extended abstract). In: IEEE Big Data, pp. 1698–1700 (2017)
Corman, J., Reutter, J.L., Savković, O.: Semantics and validation of recursive SHACL. In: Vrandečić, D., et al. (eds.) ISWC 2018. LNCS, vol. 11136, pp. 318–336. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-00671-6_19
Corman, J., Reutter, J.L., Savkovic, O.: Semantics and validation of recursive SHACL (extended version). Technical report KRDB18-1, KRDB Research Center, Free University of Bozen-Bolzano (2018). https://www.inf.unibz.it/krdb/pub/tech-rep.php
Dantsin, E., Eiter, T., Gottlob, G., Voronkov, A.: Complexity and expressive power of logic programming. ACM Comput. Surv. 33(3), 374–425 (2001)
Ekaputra, F.J., Lin, X.: SHACL4p: SHACL constraints validation within Protégé ontology editor. In: ICoDSE (2016)
Fan, W., Fan, Z., Tian, C., Dong, X.L.: Keys for graphs. PVLDB 8(12), 1590–1601 (2015)
Fan, W., Wu, Y., Xu, J.: Functional dependencies for graphs. In: SIGMOD, pp. 1843–1857 (2016)
Hansen, P., Lutz, C., Seylan, I., Wolter, F.: Efficient query rewriting in the description logic EL and beyond. In: IJCAI, pp. 3034–3040 (2015)
Horrocks, I., Giese, M., Kharlamov, E., Waaler, A.: Using semantic technology to tame the data variety challenge. IEEE Internet Comput. 20(6), 62–66 (2016)
Kharlamov, E., et al.: Capturing industrial information models with ontologies and constraints. In: Groth, P., et al. (eds.) ISWC 2016. LNCS, vol. 9982, pp. 325–343. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46547-0_30
Kharlamov, E., et al.: SOMM: industry oriented ontology management tool. In: ISWC Posters & Demos (2016)
Kharlamov, E., et al.: Ontology based data access in Statoil. J. Web Semant. 44, 3–36 (2017)
Kharlamov, E., et al.: Semantic access to streaming and static data at Siemens. J. Web Semant. 44, 54–74 (2017)
Kharlamov, E., Martín-Recuerda, F., Perry, B., Cameron, D., Fjellheim, R., Waaler, A.: Towards semantically enhanced digital twins. In: IEEE Big Data, pp. 4189–4193 (2018)
Kharlamov, E., et al.: Towards simplification of analytical workflows with semantics at Siemens (extended abstract). In: IEEE Big Data, pp. 1951–1954 (2018)
Kharlamov, E., et al.: Diagnostics of trains with semantic diagnostics rules. In: Riguzzi, F., Bellodi, E., Zese, R. (eds.) ILP 2018. LNCS (LNAI), vol. 11105, pp. 54–71. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-99960-9_4
Kharlamov, E., et al.: Semantic rules for machine diagnostics: execution and management. In: CIKM, pp. 2131–2134 (2017)
Kharlamov, E., et al.: Finding data should be easier than finding oil. In: IEEE Big Data, pp. 1747–1756 (2018)
Kharlamov, E., Zheleznyakov, D.: Capturing instance level ontology evolution for DL-Lite. In: Aroyo, L., et al. (eds.) ISWC 2011. LNCS, vol. 7031, pp. 321–337. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-25073-6_21
Kharlamov, E., Zheleznyakov, D., Calvanese, D.: Capturing model-based ontology evolution at the instance level: the case of DL-Lite. J. Comput. Syst. Sci. 79(6), 835–872 (2013)
Knublauch, H., Ryman, A.: Shapes constraint language (SHACL). W3C Recommendation, vol. 11, no. 8 (2017)
König, M., Leclère, M., Mugnier, M., Thomazo, M.: Sound, complete and minimal UCQ-rewriting for existential rules. Semant. Web 6(5), 451–475 (2015)
Mehdi, G., et al.: Semantic rule-based equipment diagnostics. In: d’Amato, C., et al. (eds.) ISWC 2017. LNCS, vol. 10588, pp. 314–333. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-68204-4_29
Mehdi, G., et al.: SemDia: semantic rule-based equipment diagnostics tool. In: CIKM, pp. 2507–2510 (2017)
Motik, B., Horrocks, I., Sattler, U.: Bridging the gap between OWL and relational databases. Web Semant. Sci. Serv. Agents World Wide Web 7(2), 74–89 (2009)
Patel-Schneider, P.F.: Using description logics for RDF constraint checking and closed-world recognition. In: AAAI (2015)
Ringsquandl, M., et al.: On event-driven knowledge graph completion in digital factories. In: IEEE Big Data, pp. 1676–1681 (2017)
Savkovic, O., Calvanese, D.: Introducing datatypes in DL-Lite. In: ECAI, pp. 720–725 (2012)
Savković, O., et al.: Semantic diagnostics of smart factories. In: Ichise, R., Lecue, F., Kawamura, T., Zhao, D., Muggleton, S., Kozaki, K. (eds.) JIST 2018. LNCS, vol. 11341, pp. 277–294. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-04284-4_19
Soylu, A., et al.: OptiqueVQS: a visual query system over ontologies for industry. Semant. Web 9(5), 627–660 (2018)
Suchanek, F.M., Kasneci, G., Weikum, G.: YAGO: a core of semantic knowledge. In: Proceedings of WWW, pp. 697–706 (2007)
Tao, J., Sirin, E., Bao, J., McGuinness, D.L.: Integrity constraints in OWL. In: AAAI (2010)
Zheleznyakov, D., Kharlamov, E., Horrocks, I.: Trust-sensitive evolution of DL-Lite knowledge bases. In: AAAI, pp. 1266–1273 (2017)
Acknowledgments
This work was partially funded by the SIRIUS Centre, Norwegian Research Council project number 237898; by the Free University of Bozen-Bolzano projects QUEST, ROBAST and ADVANCED4KG.
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
Savković, O., Kharlamov, E., Lamparter, S. (2019). Validation of SHACL Constraints over KGs with OWL 2 QL Ontologies via Rewriting. In: Hitzler, P., et al. The Semantic Web. ESWC 2019. Lecture Notes in Computer Science(), vol 11503. Springer, Cham. https://doi.org/10.1007/978-3-030-21348-0_21
Download citation
DOI: https://doi.org/10.1007/978-3-030-21348-0_21
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-21347-3
Online ISBN: 978-3-030-21348-0
eBook Packages: Computer ScienceComputer Science (R0)