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Exchange-Repairs

Managing Inconsistency in Data Exchange

  • Original Article
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Journal on Data Semantics

Abstract

In a data exchange setting with target constraints, it is often the case that a given source instance has no solutions. Intuitively, this happens when data sources contain inconsistent or conflicting information that is exposed by the target constraints at hand. In such cases, the semantics of target queries trivialize, because the certain answers of every target query over the given source instance evaluate to “true”. The aim of this paper is to introduce and explore a new framework that gives meaningful semantics in such cases using the notion of exchange-repairs. Informally, an exchange-repair of a source instance is another source instance that differs minimally from the first, but has a solution. In turn, exchange-repairs give rise to a natural notion of exchange-repair certain answers (in short, XR-certain answers) for target queries in the context of data exchange with target constraints. After exploring the structural properties of exchange-repairs, we focus on the problem of computing the XR-certain answers of conjunctive queries. We show that for schema mappings specified by source-to-target GAV dependencies and target equality-generating dependencies (egds), the XR-certain answers of a target conjunctive query can be rewritten as the consistent answers (in the sense of standard database repairs) of a union of conjunctive queries over the source schema with respect to a set of egds over the source schema, thus making it possible to use a consistent query answering system to compute XR-certain answers in data exchange. In contrast, we show that this type of rewriting is neither possible for schema mappings specified by source-to-target LAV dependencies and target egds, nor for schema mappings specified by both source-to-target and target GAV dependencies. We then examine the general case of schema mappings specified by source-to-target GLAV constraints, a weakly acyclic set of target tgds and a set of target egds. The main result asserts that, for such settings, the XR-certain answers of conjunctive queries can be rewritten as the certain answers of a union of conjunctive queries with respect to the stable models of a disjunctive logic program over a suitable expansion of the source schema.

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Notes

  1. A noteworthy alternative to symmetric difference repairs is the loosely-sound semantics of [14], discussed in detail in Sect. 3.3.

References

  1. Afrati FN, Kolaitis PG (2009) Repair checking in inconsistent databases: algorithms and complexity. In: Fagin R (ed) ICDT. ACM international conference proceeding series, vol 361. ACM, pp 31–41

  2. Alviano M, Faber W, Leone N, Perri S, Pfeifer G, Terracina G (2010) The disjunctive datalog system dlv. In: Datalog, pp 282–301

  3. Arenas M, Barceló P, Libkin L, Murlak F (2010) Relational and XML data exchange. In: Synthesis lectures on data management. Morgan & Claypool Publishers, San Rafael

  4. Arenas M, Bertossi LE, Chomicki J (1999) Consistent query answers in inconsistent databases. In: Vianu V, Papadimitriou CH (eds) PODS. ACM Press, pp 68–79

  5. Arenas M, Fagin R, Nash A (2011) Composition with target constraints. Log Methods Comput Sci 7(3:13):1–38

  6. Arenas M, Pérez J, Reutter JL, Riveros C (2013) The language of plain so-tgds: composition, inversion and structural properties. J Comput Syst Sci 79(6):763–784

    Article  MathSciNet  MATH  Google Scholar 

  7. Bertossi LE (2011) Database repairing and consistent query answering. In: Synthesis lectures on data management. Morgan & Claypool Publishers, San Rafael

  8. Bertossi LE, Chomicki J, Cortés-Calabuig A, Gutiérrez C (2002) Consistent answers from integrated data sources. In: Andreasen T, Motro A, Christiansen H, Larsen HL (eds) FQAS. Lecture notes in computer science, vol 2522. Springer, Berlin, pp 71–85

  9. Bienvenu M (2012) On the complexity of consistent query answering in the presence of simple ontologies. In: Proceedings of the twenty-sixth AAAI conference on artificial intelligence, July 22–26, 2012, Toronto, Ontario, Canada

  10. Bienvenu M, Bourgaux C, Goasdoué F (2014) Querying inconsistent description logic knowledge bases under preferred repair semantics. In: Proceedings of the twenty-eighth AAAI conference on artificial intelligence, July 27–31, 2014. Québec City, Québec, Canada, pp 996–1002

  11. Bienvenu M, Rosati R (2013) Tractable approximations of consistent query answering for robust ontology-based data access. In: IJCAI 2013, proceedings of the 23rd international joint conference on artificial intelligence, Beijing, China, August 3–9, 2013

  12. Bravo L, Bertossi LE (2003) Logic programs for consistently querying data integration systems. In: Gottlob G, Walsh T (eds) IJCAI 2003, proceedings of the eighteenth international joint conference on artificial intelligence, Acapulco, Mexico, August 9–15, pp 10–15

  13. Calì A, Lembo D, Rosati R (2003) Query rewriting and answering under constraints in data integration systems. In: Gottlob G, Walsh T (eds) IJCAI 2003, proceedings of the eighteenth international joint conference on artificial intelligence, Acapulco, Mexico, August 9–15, pp 16–21

  14. Calì A, Lembo D, Rosati R (2003) Query rewriting and answering under constraints in data integration systems. In: Gottlob and Walsh [24], pp 16–21

  15. Calvanese D, De Giacomo G, Lembo D, Lenzerini M, Poggi A, Rosati R (2007) Ontology-based database access. In: Proceedings of the fifteenth Italian symposium on advanced database systems, SEBD 2007, 17–20 June 2007. Torre Canne, Fasano, BR, Italy, pp 324–331

  16. Chomicki J, Marcinkowski J (2005) Minimal-change integrity maintenance using tuple deletions. Inf Comput 197(1–2):90–121

    Article  MathSciNet  MATH  Google Scholar 

  17. ten Cate B, Fontaine G, Kolaitis PG (2014) On the data complexity of consistent query answering. Theory Comput Syst 57(4):843–891

  18. ten Cate B, Halpert RL, Kolaitis PG (2014) Exchange-repairs: managing inconsistency in data exchange. In: Kontchakov R, Mugnier M-L (eds) RR. Lecture notes in computer science, vol 8741. Springer, Berlin, pp 140–156

  19. Duschka OM, Genesereth MR (1997) Answering recursive queries using views. In: Mendelzon AO, Özsoyoglu ZM (eds) PODS. ACM Press, pp 109–116

  20. Fagin R, Kolaitis PG, Miller RJ, Popa L (2005) Data exchange: semantics and query answering. Theor Comput Sci 336(1):89–124

    Article  MathSciNet  MATH  Google Scholar 

  21. Fagin R, Kolaitis PG, Popa L, Tan WC (2005) Composing schema mappings: second-order dependencies to the rescue. ACM Trans Database Syst 30(4):994–1055

    Article  Google Scholar 

  22. Fuxman A, Miller RJ (2007) First-order query rewriting for inconsistent databases. J Comput Syst Sci 73(4):610–635

    Article  MathSciNet  MATH  Google Scholar 

  23. Gelfond M, Lifschitz V (1988) The stable model semantics for logic programming. In: Kowalski RA, Bowen KA (eds) ICLP/SLP. MIT Press, pp 1070–1080

  24. Grahne G, Onet A (2010) Data correspondence, exchange and repair. In: Segoufin L (ed) ICDT. ACM, ACM international conference proceeding series, pp 219–230

  25. Janhunen T, Oikarinen E (2004) Capturing parallel circumscription with disjunctive logic programs. In: Alferes JJ, Leite JA (eds) JELIA. Lecture notes in computer science, vol 3229. Springer, Berlin, pp 134–146

  26. Kolaitis PG, Panttaja J, Tan WC (2006) The complexity of data exchange. In: Vansummeren S (ed) PODS. ACM, pp 30–39

  27. Krötzsch M, Rudolph S (2011) Extending decidable existential rules by joining acyclicity and guardedness. In: Walsh T (ed) IJCAI 2011, proceedings of the 22nd international joint conference on artificial intelligence, Barcelona, Catalonia, Spain, July 16–22, 2011. IJCAI/AAAI, pp 963–968

  28. Lembo D, Lenzerini M, Rosati R (2002) Source inconsistency and incompleteness in data integration. In: Borgida A, Calvanese D, Cholvy L, Rousset M (eds) Proceedings of the 9th international workshop on knowledge representation meets databases (KRDB 2002), Toulouse, France, April 21, 2002. CEUR workshop proceedings, vol 54. CEUR-WS.org

  29. Lembo D, Lenzerini M, Rosati R, Ruzzi M, Savo DF (2010) Inconsistency-tolerant semantics for description logics. In: Web reasoning and rule systems—fourth international conference, RR 2010, Bressanone/Brixen, Italy, September 22–24, 2010. Proceedings, pp 103–117

  30. Lembo D, Ruzzi M (2007) Consistent query answering over description logic ontologies. In: Marchiori M, Pan JZ, de Sainte Marie C (eds) Web reasoning and rule systems, first international conference, RR 2007, Innsbruck, Austria, June 7–8, 2007, Proceedings. Lecture notes in computer science, vol 4524. Springer, Berlin, pp 194–208

  31. Lenzerini M (2002) Data integration: a theoretical perspective. In: Popa L, Abiteboul S, Kolaitis PG (eds) PODS. ACM, pp 233–246

  32. Leone N, Pfeifer G, Faber W, Eiter T, Gottlob G, Perri S, Scarcello F (2006) The dlv system for knowledge representation and reasoning. ACM Trans Comput Log 7(3):499–562

    Article  MathSciNet  Google Scholar 

  33. Lukasiewicz T, Martinez MV, Pieris A, Simari GI (2015) From classical to consistent query answering under existential rules. In: Proceedings of the twenty-ninth AAAI conference on artificial intelligence, January 25–30, 2015, Austin, Texas, USA, pp 1546–1552

  34. Marileo MC, Bertossi LE (2010) The consistency extractor system: answer set programs for consistent query answering in databases. Data Knowl Eng 69(6):545–572

    Article  Google Scholar 

  35. Marnette B (2009) Generalized schema-mappings: from termination to tractability. In: Paredaens J, Su J (eds) PODS. ACM, pp 13–22

  36. Marnette B Resolution and datalog rewriting under value invention and equality constraints. CoRR, pp 1–12 (2012). arXiv:1212.0254

  37. Rosati R (2011) On the complexity of dealing with inconsistency in description logic ontologies. In: IJCAI 2011, proceedings of the 22nd international joint conference on artificial intelligence, Barcelona, Catalonia, Spain, July 16–22, 2011, pp 1057–1062

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Acknowledgments

The research of all authors was partially supported by NSF Grant IIS-1217869. Kolaitis’ research was also supported by the project “Handling Uncertainty in Data Intensive Applications” under the program THALES.

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Correspondence to Richard L. Halpert.

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ten Cate, B., Halpert, R.L. & Kolaitis, P.G. Exchange-Repairs. J Data Semant 5, 77–97 (2016). https://doi.org/10.1007/s13740-016-0057-4

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