Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-23T10:23:11.288Z Has data issue: false hasContentIssue false
  • English
  • Français

Consistent query answering via ASP from different perspectives: Theory and practice

Published online by Cambridge University Press:  25 January 2012

MARCO MANNA ,
FRANCESCO RICCA  and
GIORGIO TERRACINA
MARCO MANNA
Affiliation:
Department of Mathematics, University of Calabria, Cosenza, Italy (e-mail: [email protected], [email protected], [email protected])
FRANCESCO RICCA
Affiliation:
Department of Mathematics, University of Calabria, Cosenza, Italy (e-mail: [email protected], [email protected], [email protected])
GIORGIO TERRACINA
Affiliation:
Department of Mathematics, University of Calabria, Cosenza, Italy (e-mail: [email protected], [email protected], [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

A data integration system provides transparent access to different data sources by suitably combining their data, and providing the user with a unified view of them, called global schema. However, source data are generally not under the control of the data integration process; thus, integrated data may violate global integrity constraints even in the presence of locally consistent data sources. In this scenario, it may be anyway interesting to retrieve as much consistent information as possible. The process of answering user queries under global constraint violations is called consistent query answering (CQA). Several notions of CQA have been proposed, e.g., depending on whether integrated information is assumed to be sound, complete, exact, or a variant of them. This paper provides a contribution in this setting: it uniforms solutions coming from different perspectives under a common Answer-Set Programming (ASP)-based core, and provides query-driven optimizations designed for isolating and eliminating inefficiencies of the general approach for computing consistent answers. Moreover, the paper introduces some new theoretical results enriching existing knowledge on the decidability and complexity of the considered problems. The effectiveness of the approach is evidenced by experimental results.

Keywords

Answer-Set Programmingdata integrationconsistent query answering
Type
Regular Papers
Information
Theory and Practice of Logic Programming , Volume 13 , Issue 2: 25th Annual GULP Conference , March 2013 , pp. 227 - 252
Copyright
Copyright © Cambridge University Press 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abiteboul, S., Hull, R. and Vianu, V. 1995. Foundations of Databases: The Logical Level. Addison-Wesley Longman Publishing Co., Boston, MA.Google Scholar
Arenas, M., Bertossi, L. and Chomicki, J. 1999. Consistent query answers in inconsistent databases. In Proceedings of PODS'99. ACM, New York, 68–79.CrossRefGoogle Scholar
Arenas, M., Bertossi, L. and Chomicki, J. 2001. Scalar aggregation in FD-inconsistent databases. In Proceedings of ICDT'01, Bussche, J. V. den and Vianu, V., Eds. Lecture Notes in Computer Science, vol. 1973. Springer, Berlin/Heidelberg, 39–53.Google Scholar
Arenas, M., Bertossi, L. and Chomicki, J. 2003. Answer sets for consistent query answering in inconsistent databases. Theory and Practice of Logic Programming 3, 4, 393–424.CrossRefGoogle Scholar
Bertossi, L. E., Hunter, A. and Schaub, T., Eds. 2005. Inconsistency Tolerance. Lecture Notes in Computer Science, vol. 3300. Springer, Berlin/Heidelberg.CrossRefGoogle Scholar
Bry, F. 1997. Query answering in information systems with integrity constraints. In Proceedings of IICIS'97, Jajodia, S., List, W., McGregor, G. W. and Strous, L., Eds. Chapman & Hall, London, 113–130.Google Scholar
Calì, A., Calvanese, D., De Giacomo, G. and Lenzerini, M. 2002. On the role of integrity constraints in data integration. IEEE Data Engineering Bulletin 25, 3, 39–45.Google Scholar
Calì, A., Calvanese, D., De Giacomo, G. and Lenzerini, M. 2004. Data integration under integrity constraints. Information Systems 29, 2, 147–163.CrossRefGoogle Scholar
Calì, A., Lembo, D. and Rosati, R. 2003a. On the decidability and complexity of query answering over inconsistent and incomplete databases. In Proceedings of PODS'03. ACM, New York, 260–271.CrossRefGoogle Scholar
Calì, A., Lembo, D. and Rosati, R. 2003b. Query rewriting and answering under constraints in data integration systems. In Proceedings of IJCAI'03, Gottlob, G. and Walsh, T., Eds. Morgan Kaufmann Publishers, San Francisco, CA, 16–21.Google Scholar
Calì, A., Lembo, D. and Rosati, R. 2005. A comprehensive semantic framework for data integration systems. Journal of Algorithms 3, 2, 308–328.Google Scholar
Chomicki, J. and Marcinkowski, J. 2002. On the computational complexity of consistent query answers. CoRR cs.DB/0204010, 1–9.Google Scholar
Chomicki, J. and Marcinkowski, J. 2005. Minimal-change integrity maintenance using tuple deletions. Information and Computation 197, 1–2, 90–121.Google Scholar
Chomicki, J., Marcinkowski, J. and Staworko, S. 2004a. Computing consistent query answers using conflict hypergraphs. In Proceedings of CIKM'04, Grossman, D. A., Gravano, L., Zhai, C. X., Herzog, O. and Evans, D. A., Eds. ACM, New York, 417–426.CrossRefGoogle Scholar
Chomicki, J., Marcinkowski, J. and Staworko, S. 2004b. Hippo: A system for computing consistent answers to a class of SQL queries. In Advances in Database Technology – EDBT 2004, Bertino, E., Christodoulakis, S., Plexousakis, D., Christophides, V., Koubarakis, M., Böhm, K. and Ferrari, E., Eds. Lecture Notes in Computer Science, vol. 2992. Springer, Berlin/Heidelberg, 661–662.Google Scholar
Eiter, T., Fink, M., Greco, G. and Lembo, D. 2008. Repair localization for query answering from inconsistent databases. ACM Transactions on Database Systems 33, 2, 10:1–10:51.CrossRefGoogle Scholar
Eiter, T., Gottlob, G. and Mannila, H. 1997. Disjunctive datalog. ACM Transactions on Database Systems 22, 3, 364–418.Google Scholar
Faber, W., Greco, G. and Leone, N. 2007. Magic sets and their application to data integration. Journal of Computer and System Sciences 73, 4, 584–609.Google Scholar
Faber, W., Pfeifer, G. and Leone, N. 2010. Semantics and complexity of recursive aggregates in answer set programming. Artificial Intelligence In Press, Corrected Proof, 1–21.Google Scholar
Fuxman, A., Fazli, E. and Miller, R. J. 2005. ConQuer: Efficient management of inconsistent databases. In Proceedings of SIGMOD'05, Özcan, F., Ed. ACM, New York, 155–166.Google Scholar
Fuxman, A. and Miller, R. J. 2007. First-order query rewriting for inconsistent databases. Journal of Computer and System Sciences 73, 4, 610–635. Special Issue: Database Theory 2005.Google Scholar
Garcia-Molina, H., Papakonstantinou, Y., Quass, D., Rajaraman, A., Sagiv, Y., Ullman, J., Vassalos, V. and Widom, J. 1997. The TSIMMIS approach to mediation: Data models and languages. Journal of Intelligent Information Systems 8, 2, 117–132.Google Scholar
Gelfond, M. and Lifschitz, V. 1988. The stable model semantics for logic programming. In Proceedings of ICLP/SLP'88, Kowalski, R. A. and Bowen, K. A., Eds. MIT Press, Cambridge, MA, 1070–1080.Google Scholar
Gelfond, M. and Lifschitz, V. 1991. Classical negation in logic programs and disjunctive databases. New Generation Computing 9, 3–4, 365–385.CrossRefGoogle Scholar
Goh, C. H., Bressan, S., Madnick, S. and Siegel, M. 1999. Context interchange: New features and formalisms for the intelligent integration of information. ACM Transactions on Information Systems 17, 3, 270–293.Google Scholar
Greco, G., Greco, S. and Zumpano, E. 2001. A logic programming approach to the integration, repairing and querying of inconsistent databases. In Proceedings of ICLP'01, Codognet, P., Ed. Lecture Notes in Computer Science, vol. 17. Springer, Berlin/Heidelberg, 348–364.Google Scholar
Greco, S. and Zumpano, E. 2000. Querying inconsistent databases. In Proceedings of LPAR'00, Parigot, M. and Voronkov, A., Eds. Springer-Verlag, Berlin/Heidelberg, 308–325.Google Scholar
Grieco, L., Lembo, D., Rosati, R. and Ruzzi, M. 2005. Consistent query answering under key and exclusion dependencies: Algorithms and experiments. In Proceedings of CIKM'05, Herzog, O., Schek, H.-J., Fuhr, N., Chowdhury, A. and Teiken, W., Eds. ACM, New York, 792–799.Google Scholar
Lembo, D. 2004. Dealing with Inconsistency and Incompleteness in Data Integration. PhD Thesis, Dipartimento di Informatica e Sistemistica, Universitaà di Roma “La Sapienza”.Google Scholar
Lenzerini, M. 2002. Data integration: A theoretical perspective. In Proceedings of PODS'02, Popa, L., Ed. ACM, New York, 233–246.Google Scholar
Leone, N., Greco, G., Ianni, G., Lio, V., Terracina, G., Eiter, T., Faber, W., Fink, M., Gottlob, G., Rosati, R., Lembo, D., Lenzerini, M., Ruzzi, M., Kalka, E., Nowicki, B. and Staniszkis, W. 2005. The INFOMIX system for advanced integration of incomplete and inconsistent data. In Proceedings of SIGMOD'05, Özcan, F., Ed. ACM, New York, 915–917.CrossRefGoogle Scholar
Leone, N., Pfeifer, G., Faber, W., Eiter, T., Gottlob, G., Perri, S. and Scarcello, F. 2006. The DLV system for knowledge representation and reasoning. ACM Transactions on Computational Logic 7, 3, 499–562.CrossRefGoogle Scholar
Levene, M. and Vincent, M. W. 2000. Justification for inclusion dependency normal form. IEEE Transactions on Knowledge and Data Engineering 12, 2, 281–291.Google Scholar
Manna, M., Ricca, F. and Terracina, G. 2011. Consistent query answering via ASP from different perspectives: Theory and practice. CoRR cs.DB/1107.4570, 1–30.Google Scholar
Marileo, M. C. and Bertossi, L. E. 2010. The consistency extractor system: Answer set programs for consistent query answering in databases. Data and Knowledge Engineering 69, 6, 545–572.Google Scholar
Minker, J. 1982. On indefinite data bases and the closed world assumption. In Proceedings of CADE'82, Loveland, D. W., Ed. Lecture Notes in Computer Science, vol. 138. Springer, Berlin/Heidelberg, 292–308.Google Scholar
Terracina, G., De Francesco, E., Panetta, C. and Leone, N. 2008. Enhancing a DLP system for advanced database applications. In Proceedings of RR'08, Calvanese, D. and Lausen, G., Eds. Lecture Notes in Computer Science, vol. 5341. Springer, Berlin/Heidelberg, 119–134.Google Scholar
Terracina, G., Leone, N., Lio, V. and Panetta, C. 2008. Experimenting with recursive queries in database and logic programming systems. Theory and Practice of Logic Programming 8, 2, 129–165.CrossRefGoogle Scholar
Tomasic, A., Raschid, L. and Valduriez, P. 1998. Scaling access to heterogeneous data sources with DISCO. IEEE Transactions on Knowledge and Data Engineering 10, 5, 808–823.CrossRefGoogle Scholar