Dynamic Querying of Mass-Storage RDF Data with Rule-Based Entailment Regimes

  • Giovambattista Ianni
  • Thomas Krennwallner
  • Alessandra Martello
  • Axel Polleres
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5823)


RDF Schema (RDFS) as a lightweight ontology language is gaining popularity and, consequently, tools for scalable RDFS inference and querying are needed. SPARQL has become recently a W3C standard for querying RDF data, but it mostly provides means for querying simple RDF graphs only, whereas querying with respect to RDFS or other entailment regimes is left outside the current specification. In this paper, we show that SPARQL faces certain unwanted ramifications when querying ontologies in conjunction with RDF datasets that comprise multiple named graphs, and we provide an extension for SPARQL that remedies these effects. Moreover, since RDFS inference has a close relationship with logic rules, we generalize our approach to select a custom ruleset for specifying inferences to be taken into account in a SPARQL query. We show that our extensions are technically feasible by providing benchmark results for RDFS querying in our prototype system GiaBATA, which uses Datalog coupled with a persistent Relational Database as a back-end for implementing SPARQL with dynamic rule-based inference. By employing different optimization techniques like magic set rewriting our system remains competitive with state-of-the-art RDFS querying systems.


Resource Description Framework Graph Pattern SPARQL Query Resource Description Framework Data Resource Description Framework Graph 
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.
    Klyne, G., Carroll, J.J. (eds.): Resource Description Framework (RDF): Concepts and Abstract Syntax. W3C Rec. (February 2004)Google Scholar
  2. 2.
    Brickley, D., Miller, L.: FOAF Vocabulary Specification 0.91 (2007),
  3. 3.
    Bojãrs, U., Breslin, J.G., Berrueta, D., Brickley, D., Decker, S., Fernández, S., Görn, C., Harth, A., Heath, T., Idehen, K., Kjernsmo, K., Miles, A., Passant, A., Polleres, A., Polo, L., Sintek, M.: SIOC Core Ontology Specification. W3C member submission (June 2007) Google Scholar
  4. 4.
    Suchanek, F.M., Kasneci, G., Weikum, G.: Yago: A Core of Semantic Knowledge. In: WWW 2007. ACM, New York (2007)Google Scholar
  5. 5.
    ter Horst, H.J.: Completeness, decidability and complexity of entailment for RDF Schema and a semantic extension involving the OWL vocabulary. J. Web Semant. 3(2–3), 79–115 (2005)Google Scholar
  6. 6.
    Muñoz, S., Pérez, J., Gutierrez, C.: Minimal deductive systems for RDF. In: Franconi, E., Kifer, M., May, W. (eds.) ESWC 2007. LNCS, vol. 4519, pp. 53–67. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  7. 7.
    Hogan, A., Harth, A., Polleres, A.: Scalable authoritative owl reasoning for the web. Int. J. Semant. Web Inf. Syst. 5(2) (2009)Google Scholar
  8. 8.
    Polleres, A., Scharffe, F., Schindlauer, R.: SPARQL++ for mapping between RDF vocabularies. In: ODBASE 2007, pp. 878–896. Springer, Heidelberg (2007)Google Scholar
  9. 9.
    Harth, A., Umbrich, J., Hogan, A., Decker, S.: YARS2: A Federated Repository For Querying Graph Structured Data from the Web. In: Aberer, K., Choi, K.-S., Noy, N., Allemang, D., Lee, K.-I., Nixon, L.J.B., Golbeck, J., Mika, P., Maynard, D., Mizoguchi, R., Schreiber, G., Cudré-Mauroux, P. (eds.) ASWC 2007 and ISWC 2007. LNCS, vol. 4825, pp. 211–224. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  10. 10.
    Prud’hommeaux, E., Seaborne, A. (eds.): SPARQL Query Language for RDF. W3C Rec. (January 2008)Google Scholar
  11. 11.
    Polleres, A.: From SPARQL to rules (and back). In: WWW 2007, pp. 787–796. ACM, New York (2007)CrossRefGoogle Scholar
  12. 12.
    Angles, R., Gutierrez, C.: The expressive power of SPARQL. In: Sheth, A.P., Staab, S., Dean, M., Paolucci, M., Maynard, D., Finin, T., Thirunarayan, K. (eds.) ISWC 2008. LNCS, vol. 5318, pp. 114–129. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  13. 13.
    Leone, N., Pfeifer, G., Faber, W., Eiter, T., Gottlob, G., Perri, S., Scarcello, F.: The DLV system for knowledge representation and reasoning. ACM Trans. Comput. Log. 7(3), 499–562 (2006)Google Scholar
  14. 14.
    Euzenat, J., Polleres, A., Scharffe, F.: Processing ontology alignments with SPARQL. In: OnAV 2008 Workshop, CISIS 2008, pp. 913–917. IEEE Computer Society, Los Alamitos (2008)Google Scholar
  15. 15.
    Ianni, G., Krennwallner, T., Martello, A., Polleres, A.: A Rule Systemfor Querying Persistent RDFS Data. In: Aroyo, L., Traverso, P., Ciravegna, F., Cimiano, P., Heath, T., Hyvönen, E., Mizoguchi, R., Oren, E., Sabou, M., Simperl, E. (eds.) ESWC 2009. LNCS, vol. 5554, pp. 857–862. Springer, Heidelberg (2009)Google Scholar
  16. 16.
    Guo, Y., Pan, Z., Heflin, J.: LUBM: A Benchmark for OWL Knowledge Base Systems. J. Web Semant. 3(2–3), 158–182 (2005)Google Scholar
  17. 17.
    Motik, B., Grau, B.C., Horrocks, I., Wu, Z., Fokoue, A., Lutz, C. (eds.): OWL 2 Web Ontology Language Profiles W3C Cand. Rec. (June 2009)Google Scholar
  18. 18.
    Pérez, J., Arenas, M., Gutierrez, C.: Semantics and complexity of SPARQL. In: Cruz, I., Decker, S., Allemang, D., Preist, C., Schwabe, D., Mika, P., Uschold, M., Aroyo, L.M. (eds.) ISWC 2006. LNCS, vol. 4273, pp. 30–43. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  19. 19.
    Polleres, A., Schindlauer, R.: dlvhex-sparql: A SPARQL-compliant query engine based on dlvhex. In: ALPSWS 2007. CEUR-WS, pp. 3–12 (2007)Google Scholar
  20. 20.
    Hayes, P.: RDF semantics. W3C Rec. (February 2004)Google Scholar
  21. 21.
    Ianni, G., Martello, A., Panetta, C., Terracina, G.: Efficiently querying RDF(S) ontologies with answer set programming. J. Logic Comput. 19(4), 671–695 (2009)zbMATHCrossRefMathSciNetGoogle Scholar
  22. 22.
    de Bruijn, J.: SemanticWeb Language Layering with Ontologies, Rules, and Meta-Modeling. PhD thesis, University of Innsbruck (2008) Google Scholar
  23. 23.
    Boley, H., Kifer, M.: RIF Basic Logic Dialect. W3C Working Draft (July 2009)Google Scholar
  24. 24.
    Eiter, T., Ianni, G., Schindlauer, R., Tompits, H.: Effective integration of declarative rules with external evaluations for semantic-web reasoning. In: Sure, Y., Domingue, J. (eds.) ESWC 2006. LNCS, vol. 4011, pp. 273–287. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  25. 25.
    Terracina, G., Leone, N., Lio, V., Panetta, C.: Experimenting with recursive queries in database and logic programming systems. Theory Pract. Log. Program. 8(2), 129–165 (2008)zbMATHMathSciNetCrossRefGoogle Scholar
  26. 26.
    Theoharis, Y., Christophides, V., Karvounarakis, G.: Benchmarking Database Representations of RDF/S Stores. In: Gil, Y., Motta, E., Benjamins, V.R., Musen, M.A. (eds.) ISWC 2005. LNCS, vol. 3729, pp. 685–701. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  27. 27.
    Abadi, D.J., Marcus, A., Madden, S., Hollenbach, K.J.: Scalable Semantic Web Data Management Using Vertical Partitioning. In: VLDB, pp. 411–422. ACM, New York (2007)Google Scholar
  28. 28.
    Beeri, C., Ramakrishnan, R.: On the power of magic. J. Log. Program. 10(3-4), 255–299 (1991)zbMATHCrossRefMathSciNetGoogle Scholar
  29. 29.
    Lu, J., Cao, F., Ma, L., Yu, Y., Pan, Y.: An Effective SPARQL Support over Relational Databases. In: SWDB-ODBIS, pp. 57–76 (2007)Google Scholar
  30. 30.
    Bonner, A.J.: Hypothetical datalog: complexity and expressibility. Theor. Comp. Sci. 76(1), 3–51 (1990)zbMATHCrossRefMathSciNetGoogle Scholar
  31. 31.
    Guti´errez, C., Hurtado, C.A., Mendelzon, A.O.: Foundations of semantic web databases. In: PODS 2004, pp. 95–106. ACM, New York (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Giovambattista Ianni
    • 1
  • Thomas Krennwallner
    • 2
  • Alessandra Martello
    • 1
  • Axel Polleres
    • 3
  1. 1.Dipartimento di MatematicaUniversità della CalabriaRendeItaly
  2. 2.Institut für Informationssysteme 184/3Technische Universität WienAustria
  3. 3.Digital Enterprise Research InstituteNational University of IrelandGalway

Personalised recommendations