ABSTRACT
The notion of representation systems describes structures that are algebraically closed under queries. It has recently been realized that representation systems are highly relevant also in the context of data exchange. We extend the notion of representation system to encompass data exchange mappings and their composition. Seen through this lens, two major classes of representation systems emerge, namely homomorphic data exchange systems and strong data exchange systems. The homomorphic "OWA" systems encompass the "classical" part of data exchange. Reasoning is modulo homomorphic equivalence (CQ-equivalence), and only unions of conjunctive queries and monotone data exchange mappings are supported.
We then develop some new technical tools that allow us to prove that there is a class of '"CWA" strong representation systems in which reasoning is modulo isomorphic equivalence. These systems are based on conditional tables, and they support first order queries and non-monotonic data exchange mappings specified by a large class of second order dependencies. We achieve this by showing that, under a CWA-interpretation, conditional tables are chaseable with the aforementioned class of second order dependencies, and that the class is closed under composition in the CWA-setting.
We also introduce a stricter notion of composability, and show that the class of (first order) source-to-target tuple generating dependencies is closed under the stricter notion of composability.
- S. Abiteboul, R. Hull, and V. Vianu. Foundations of Databases. Addison-Wesley, 1995. Google ScholarDigital Library
- S. Abiteboul, P. C. Kanellakis, and G. Grahne. On the representation and querying of sets of possible worlds. Theor. Comput. Sci., 78(1):158--187, 1991. Google ScholarDigital Library
- M. Arenas, R. Fagin, and A. Nash. Composition with target constraints. In ICDT, pages 129--142, 2010. Google ScholarDigital Library
- M. Arenas, J. Pérez, and J. L. Reutter. Data exchange beyond complete data. In PODS, pages 83--94, 2011. Google ScholarDigital Library
- M. Arenas, J. Pérez, J. L. Reutter, and C. Riveros. Composition and inversion of schema mappings. SIGMOD Record, 38(3):17--28, 2009. Google ScholarDigital Library
- M. Arenas, J. Pérez, and C. Riveros. The recovery of a schema mapping: Bringing exchanged data back. ACM Trans. Database Syst., 34(4), 2009. Google ScholarDigital Library
- P. C. Arocena, A. Fuxman, and R. J. Miller. Composing local-as-view mappings: closure and applications. In ICDT, pages 209--218, 2010. Google ScholarDigital Library
- P. A. Bernstein. Applying model management to classical meta data problems. In CIDR, 2003.Google Scholar
- A. Calì, G. Gottlob, and M. Kifer. Taming the infinite chase: Query answering under expressive relational constraints. In KR, pages 70--80, 2008.Google Scholar
- A. Deutsch, A. Nash, and J. B. Remmel. The chase revisited. In PODS, pages 149--158, 2008. Google ScholarDigital Library
- R. Fagin. Horn clauses and database dependencies. J. ACM, 29(4):952--985, 1982. Google ScholarDigital Library
- R. Fagin. Inverting schema mappings. ACM Trans. Database Syst., 32(4), 2007. Google ScholarDigital Library
- R. Fagin, P. G. Kolaitis, R. J. Miller, and L. Popa. Data exchange: Semantics and query answering. In ICDT, pages 207--224, 2003. Google ScholarDigital Library
- R. Fagin, P. G. Kolaitis, A. Nash, and L. Popa. Towards a theory of schema-mapping optimization. In PODS, pages 33--42, 2008. Google ScholarDigital Library
- R. Fagin, P. G. Kolaitis, and L. Popa. Data exchange: getting to the core. In PODS, pages 90--101, 2003. Google ScholarDigital Library
- R. Fagin, P. G. Kolaitis, L. Popa, and W. C. Tan. Composing schema mappings: Second-order dependencies to the rescue. In PODS, pages 83--94, 2004. Google ScholarDigital Library
- R. Fagin, P. G. Kolaitis, L. Popa, and W. C. Tan. Reverse data exchange: coping with nulls. In PODS, pages 23--32, 2009. Google ScholarDigital Library
- G. Grahne. The Problem of Incomplete Information in Relational Databases, volume 554 of Lecture Notes in Computer Science. Springer, 1991. Google ScholarDigital Library
- G. Grahne and V. Kiricenko. Towards an algebraic theory of information integration. Inf. Comput., 194(2):79--100, 2004. Google ScholarDigital Library
- G. Grahne and A. Onet. Data correspondence, exchange and repair. In ICDT, pages 219--230, 2010. Google ScholarDigital Library
- G. Grahne and A. Onet. Closed world chasing. In LID, pages 7--14, 2011. Google ScholarDigital Library
- A. Hernich. Answering non-monotonic queries in relational data exchange. In ICDT, pages 143--154, 2010. Google ScholarDigital Library
- A. Hernich and N. Schweikardt. Cwa-solutions for data exchange settings with target dependencies. In PODS, pages 113--122, 2007. Google ScholarDigital Library
- T. Imielinski and W. L. Jr. Incomplete information in relational databases. J. ACM, 31(4):761--791, 1984. Google ScholarDigital Library
- G. Karvounarakis and V. Tannen. Conjunctive queries and mappings with unequalities. In Technical Reports (CIS), pages 1--15, 2008.Google Scholar
- L. Libkin. Data exchange and incomplete information. In PODS, pages 60--69, 2006. Google ScholarDigital Library
- L. Libkin. Incomplete information and certain answers in general data models. In PODS, pages 59--70, 2011. Google ScholarDigital Library
- L. Libkin and C. Sirangelo. Open and closed world assumptions in data exchange. In Description Logics, 2009.Google Scholar
- A. Nash, P. A. Bernstein, and S. Melnik. Composition of mappings given by embedded dependencies. ACM Trans. Database Syst., 32(1):4, 2007. Google ScholarDigital Library
Index Terms
- Representation systems for data exchange
Recommendations
Data exchange beyond complete data
In the traditional data exchange setting, source instances are restricted to be complete in the sense that every fact is either true or false in these instances. Although natural for a typical database translation scenario, this restriction is gradually ...
Data exchange beyond complete data
PODS '11: Proceedings of the thirtieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systemsIn the traditional data exchange setting, source instances are restricted to be complete in the sense that every fact is either true or false in these instances. Although natural for a typical database translation scenario, this restriction is gradually ...
Data exchange: semantics and query answering
Database theoryData exchange is the problem of taking data structured under a source schema and creating an instance of a target schema that reflects the source data as accurately as possible. In this paper, we address foundational and algorithmic issues related to ...
Comments