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Provenance for SPARQL Queries

  • Carlos Viegas Damásio
  • Anastasia Analyti
  • Grigoris Antoniou
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7649)

Abstract

Determining trust of data available in the Semantic Web is fundamental for applications and users, in particular for linked open data obtained from SPARQL endpoints. There exist several proposals in the literature to annotate SPARQL query results with values from abstract models, adapting the seminal works on provenance for annotated relational databases. We provide an approach capable of providing provenance information for a large and significant fragment of SPARQL 1.1, including for the first time the major non-monotonic constructs under multiset semantics. The approach is based on the translation of SPARQL into relational queries over annotated relations with values of the most general m-semiring, and in this way also refuting a claim in the literature that the OPTIONAL construct of SPARQL cannot be captured appropriately with the known abstract models.

Keywords

How-provenance SPARQL queries m-semirings difference 

References

  1. 1.
    SPARQL 1.1 query language, 2012. W3C Working Draft (January 05, 2012), http://www.w3.org/TR/2012/WD-sparql11-query-20120105/
  2. 2.
    Amer, K.: Equationally complete classes of commutative monoids with monus. Algebra Universalis 18, 129–131 (1984)MathSciNetzbMATHCrossRefGoogle Scholar
  3. 3.
    Antoine Zimmermann, A.P., Lopes, N., Straccia, U.: A general framework for representing, reasoning and querying with annotated semantic web data. Journal of Web Semantics 11, 72–95 (2012)CrossRefGoogle Scholar
  4. 4.
    Buneman, P., Kostylev, E.V.: Annotation algebras for RDFS. In: Proc. of the 2nd Int. Ws. on the Role of Semantic Web in Provenance Management (SWPM 2010). CEUR Workshop Proceedings (2010)Google Scholar
  5. 5.
    Dividino, R., Sizov, S., Staab, S., Schueler, B.: Querying for provenance, trust, uncertainty and other meta knowledge in RDF. Web Semant. 7(3), 204–219 (2009)CrossRefGoogle Scholar
  6. 6.
    Elliott, B., Cheng, E., Thomas-Ogbuji, C., Ozsoyoglu, Z.M.: A complete translation from SPARQL into efficient SQL. In: Proc. of the 2009 Int. Database Engineering & Applications Symposium, IDEAS 2009, pp. 31–42. ACM (2009)Google Scholar
  7. 7.
    Flouris, G., Fundulaki, I., Pediaditis, P., Theoharis, Y., Christophides, V.: Coloring RDF Triples to Capture Provenance. In: Bernstein, A., Karger, D.R., Heath, T., Feigenbaum, L., Maynard, D., Motta, E., Thirunarayan, K. (eds.) ISWC 2009. LNCS, vol. 5823, pp. 196–212. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  8. 8.
    Geerts, F., Poggi, A.: On database query languages for K-relations. J. Applied Logic 8(2), 173–185 (2010)MathSciNetzbMATHCrossRefGoogle Scholar
  9. 9.
    Green, T.J., Karvounarakis, G., Tannen, V.: Provenance semirings. In: Proc. of PODS 2007, pp. 31–40. ACM, New York (2007)Google Scholar
  10. 10.
    Pérez, J., Arenas, M., Gutierrez, C.: Semantics and complexity of SPARQL. ACM Trans. Database Syst. 34(3), 16:1–16:45 (2009)Google Scholar
  11. 11.
    Polleres, A.: From SPARQL to rules (and back). In: Williamson, C.L., Zurko, M.E., Patel-Schneider, P.F., Shenoy, P.J. (eds.) Proc. of the 16th Int. Conf. on World Wide Web, WWW 2007, pp. 787–796. ACM (2007)Google Scholar
  12. 12.
    Theoharis, Y., Fundulaki, I., Karvounarakis, G., Christophides, V.: On provenance of queries on semantic web data. IEEE Internet Computing 15(1), 31–39 (2011)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Carlos Viegas Damásio
    • 1
  • Anastasia Analyti
    • 2
  • Grigoris Antoniou
    • 2
    • 3
  1. 1.CENTRIA, Departamento de Informática Faculdade de Ciências e TecnologiaUniversidade Nova de LisboaCaparicaPortugal
  2. 2.Institute of Computer ScienceFORTH-ICSCreteGreece
  3. 3.Department of Computer ScienceUniversity of CreteCreteGreece

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