Query Answering under Non-guarded Rules in Datalog+/-

  • Andrea Calì
  • Georg Gottlob
  • Andreas Pieris
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6333)

Abstract

In ontology-based data access, an extensional database is enhanced by an ontology that generates new intensional knowledge which has to be considered when answering queries. In this setting, tractable data complexity (i.e., complexity w.r.t. the data only) of query answering is crucial, given the need to deal with large data sets. A well-known class of tractable ontology languages is the DL-lite family; however, in DL-lite it is impossible to express simple and useful integrity constraints that involve joins. To overcome this limitation, the Datalog+/- class of decidable languages uses tuple-generating dependencies (TGDs) as rules, thus allowing for conjunctions of atoms in the rule bodies, with suitable limitations to ensure decidability. In particular, sticky sets of TGDs allow for joins and variable repetition in rule bodies under certain conditions. In this paper we extend the notion of stickiness by introducing weakly-sticky sets of TGDs, which also generalize the well-known weakly-acyclic sets of TGDs. We investigate the complexity of query answering under such language, and in addition we provide novel complexity results on weakly-acyclic sets of TGDs. Moreover, we present the novel class of sticky-join sets of TGDs, which generalizes both sticky sets of TGDs and so-called linear TGDs, an extension of inclusion dependencies.

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References

  1. 1.
    Abiteboul, S., Hull, R., Vianu, V.: Foundations of Databases. Addison-Wesley, ReadingGoogle Scholar
  2. 2.
    Baget, J.-F., Leclère, M., Mugnier, M.-L., Salvat, E.: Extending decidable cases for rules with existential variables. In: Proc. of IJCAI, pp. 677–682 (2009)Google Scholar
  3. 3.
    Beeri, C., Vardi, M.Y.: The implication problem for data dependencies. In: Proc. of ICALP, pp. 73–85 (1981)Google Scholar
  4. 4.
    Cabibbo, L.: The expressive power of stratified logic programs with value invention. Inf. Comput. 147(1), 22–56 (1998)MATHCrossRefMathSciNetGoogle Scholar
  5. 5.
    Calì, A., Gottlob, G., Kifer, M.: Taming the infinite chase: Query answering under expressive relational constraints. In: Proc. of KR, pp. 70–80 (2008)Google Scholar
  6. 6.
    Calì, A., Gottlob, G., Lukasiewicz, T.: Datalog± A unified approach to ontologies and integrity constraints. In: Proc. of ICDT, pp. 14–30 (2009)Google Scholar
  7. 7.
    Calì, A., Gottlob, G., Lukasiewicz, T.: A general datalog-based framework for tractable query answering over ontologies. In: Proc. of PODS, pp. 77–86 (2009)Google Scholar
  8. 8.
    Calì, A., Gottlob, G., Pieris, A.: Advanced processing for ontological queries. In: Proc. of VLDB (to appear, 2010)Google Scholar
  9. 9.
    Calì, A., Gottlob, G., Pieris, A.: Advanced processing for ontological queries (2010), http://benner.dbai.tuwien.ac.at/staff/gottlob/CGP.pdf
  10. 10.
    Calì, A., Gottlob, G., Pieris, A.: Ontological reasoning with F-Logic Lite and its extensions. In: Proc. of AAAI (to appear, 2010)Google Scholar
  11. 11.
    Calì, A., Lembo, D., Rosati, R.: On the decidability and complexity of query answering over inconsistent and incomplete databases. In: Proc. of PODS, pp. 260–271 (2003)Google Scholar
  12. 12.
    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)MATHCrossRefGoogle Scholar
  13. 13.
    Dantsin, E., Eiter, T., Georg, G., Voronkov, A.: Complexity and expressive power of logic programming. ACM Comput. Surv. 33(3), 374–425 (2001)CrossRefGoogle Scholar
  14. 14.
    Deutsch, A., Nash, A., Remmel, J.B.: The chase revisisted. In: Proc. of PODS, pp. 149–158 (2008)Google Scholar
  15. 15.
    Deutsch, A., Tannen, V.: Reformulation of XML queries and constraints. In: Proc. of ICDT, pp. 225–241 (2003)Google Scholar
  16. 16.
    Fagin, R., Kolaitis, P.G., Miller, R.J., Popa, L.: Data exchange: Semantics and query answering. Theor. Comput. Sci. 336(1), 89–124 (2005)MATHCrossRefMathSciNetGoogle Scholar
  17. 17.
    Johnson, D.S., Klug, A.C.: Testing containment of conjunctive queries under functional and inclusion dependencies. J. Comput. Syst. Sci. 28(1), 167–189 (1984)MATHCrossRefMathSciNetGoogle Scholar
  18. 18.
    Kolaitis, P.G., Panttaja, J.: Personal Communication (2009)Google Scholar
  19. 19.
    Kolaitis, P.G., Panttaja, J., Tan, W.-C.: The complexity of data exchange. In: Proc. of PODS, pp. 30–39 (2006)Google Scholar
  20. 20.
    Maier, D., Mendelzon, A.O., Sagiv, Y.: Testing implications of data dependencies. ACM Trans. Database Syst. 4(4), 455–469 (1979)CrossRefGoogle Scholar
  21. 21.
    Mailharrow, D.: A classification and constraint-based framework for configuration. Artif. Intell. for Engineering Design, Analysis and Manufacturing 12(4), 383–397 (1998)Google Scholar
  22. 22.
    Panttaya, J.: Complexity in databases, games, and logics. PhD thesis, University of California Santa Cruz (2006)Google Scholar
  23. 23.
    Patel-Schneider, P.F., Horrocks, I.: A comparison of two modelling paradigms in the semantic web. J. Web Semantics 5(4), 240–250 (2007)Google Scholar
  24. 24.
    Poggi, A., Lembo, D., Calvanese, D., De Giacomo, G., Lenzerini, M., Rosati, R.: Linking data to ontologies. J. Data Semantics 10, 133–173 (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Andrea Calì
    • 3
    • 2
  • Georg Gottlob
    • 1
    • 2
  • Andreas Pieris
    • 1
  1. 1.Computing LaboratoryUniversity of OxfordUK
  2. 2.Oxford-Man Institute of Quantitative FinanceUniversity of OxfordUK
  3. 3.Department of Information Systems and ComputingBrunel UniversityUK

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