ABSTRACT
Data exchange and virtual data integration have been the subject of several investigations in the recent literature. At the same time, the notion of peer data management has emerged as a powerful abstraction of many forms of flexible and dynamic data-centere ddistributed systems. Although research on the above issues has progressed considerably in the last years, a clear understanding on how to combine data exchange and data integration in peer data management is still missing. This is the subject of the present paper. We start our investigation by first proposing a novel framework for peer data exchange, showing that it is a generalization of the classical data exchange setting. We also present algorithms for all the relevant data exchange tasks, and show that they can all be done in polynomial time with respect to data complexity. Based on the motivation that typical mappings and integrity constraints found in data integration are not captured by peer data exchange, we extend the framework to incorporate these features. One of the main difficulties is that the constraints of this new class are not amenable to materialization. We address this issue by resorting to a suitable combination of virtual and materialized data exchange, showing that the resulting framework is a generalization of both classical data exchange and classical data integration, and that the new setting incorporates the most expressive types of mapping and constraints considered in the two contexts. Finally, we present algorithms for all the relevant data management tasks also in the new setting, and show that, again, their data complexity is polynomial.
- S. Abiteboul and O. Duschka. Complexity of answering queries using materialized views. In Proc. of PODS'98, pages 254--265, 1998. Google Scholar
Digital Library
- S. Abiteboul, R. Hull, and V. Vianu. Foundations of Databases. Addison Wesley Publ. Co., 1995. Google Scholar
Digital Library
- M. Arenas, P. Barcelo, R. Fagin, and L. Libkin. Locally consistent transformations and query answering in data exchange. In Proc. of PODS 2004, pages 229--240, 2004. Google Scholar
Digital Library
- M. Arenas, V. Kantere, A. Kementsietsidis, I. Kiringa, R. J. Miller, and J. Mylopoulos. The Hyperion pro ject: from data integration to data coordination. SIGMOD Record, 32(3):53--58, 2003. Google Scholar
Digital Library
- M. Arenas and L. Libkin. XML data exchange: consistency and query answering. In Proc. of PODS 2005, pages 13--24, 2005. Google Scholar
Digital Library
- P. A. Bernstein, F. Giunchiglia, A. Kementsietsidis, J. Mylopoulos, L. Serafini, and I. Zaihrayeu. Data management for peer-to-peer computing: A vision. In Proc. of WebDB 2002, 2002.Google Scholar
- L. Bravo and L. Bertossi. Logic programming for consistently querying data integration systems. In Proc. of IJCAI 2003, pages 10--15, 2003. Google Scholar
Digital Library
- A. Calì, D. Calvanese, G. De Giacomo, and M. Lenzerini. Data integration under integrity constraints. Information Systems, 29:147--163, 2004. Google Scholar
Digital Library
- A. Calì, D. Lembo, and R. Rosati. On the decidability and complexity of query answering over inconsistent and incomplete databases. In Proc. of PODS 2003, pages 260--271, 2003. Google Scholar
Digital Library
- A. Calì, D. Lembo, and R. Rosati. Query rewriting and answering under constraints in data integration systems. In Proc. of IJCAI 2003, pages 16--21, 2003.Google Scholar
Digital Library
- D. Calvanese, G. De Giacomo, D. Lembo, M. Lenzerini, and R. Rosati. Inconsistency tolerance in P2P data integration: an epistemic logic approach. In Proc. of DBPL 2005, pages 90--105, 2005. Google Scholar
Digital Library
- D. Calvanese, G. De Giacomo, M. Lenzerini, and R. Rosati. Logical foundations of peer-to-peer data integration. In Proc. of PODS 2004, pages 241--251, 2004. Google Scholar
Digital Library
- P. Chatalic, G. -H. Nguyen, and M. -C. Rousset. Reasoning with inconsistencies in propositional Peer-to-Peer inference systems. In Proc. of ECAI 2006, pages 352--357, 2006. Google Scholar
Digital Library
- R. Fagin, P. G. Kolaitis, R. J. Miller, and L. Popa. Data exchange: Semantics and query answering. Theor. Comp. Sci., 336(1):89--124, 2005. Google Scholar
Digital Library
- R. Fagin, P. G. Kolaitis, and L. Popa. Data exchange: Getting to the core. ACM Trans. on Database Systems, 30(1):174--210, 2005. Google Scholar
Digital Library
- R. Fagin, P. G. Kolaitis, L. Popa, and W. -C. Tan. Composing schema mappings: Second-order dependencies to the rescue. ACM Trans. on Database Systems, 30(4):994--1055, 2005. Google Scholar
Digital Library
- E. Franconi, G. Kuper, A. Lopatenko, and L. Serafini. A robust logical and computational characterisation of peer-to-peer database systems. In Proc. of the VLDB International Workshop On Databases, Information Systems and Peer-to-Peer Computing (DBISP2P 2003), 2003.Google Scholar
- A. Fuxman, P. G. Kolaitis, R. Miller, and W. C. Tan. Peer data exchange. In Proc. of PODS 2005, pages 160--171, 2005. Google Scholar
Digital Library
- G. Gottlob. Computing cores for data exchange: New algorithms and practical solutions. In Proc. of PODS 2005, pages 148--159, 2005. Google Scholar
Digital Library
- G. Gottlob and A. Nash. Data exchange: computing cores in polynomial time. In Proc. of PODS 2006, pages 40--49, 2006. Google Scholar
Digital Library
- S. Gribble, A. Halevy, Z. Ives, M. Rodrig, and D. Suciu. What can databases do for peer-to-peer? In Proc. of WebDB 2001, 2001.Google Scholar
- A. Halevy, Z. Ives, D. Suciu, and I. Tatarinov. Schema mediation in peer data management systems. In Proc. of ICDE 2003, pages 505--516, 2003.Google Scholar
Cross Ref
- A. Y. Halevy. Answering queries using views: A survey. VLDB Journal, 10(4):270--294, 2001. Google Scholar
Digital Library
- A. Y. Halevy, A. Ra jaraman, and J. Ordille. Data integration: The teenage years. In Proc. of VLDB 2006, pages 9--16, 2006. Google Scholar
Digital Library
- P. G. Kolaitis. Schema mappings, data exchange, and metadata management. In Proc. of PODS 2005, pages 61--75, 2005. Google Scholar
Digital Library
- P. G. Kolaitis, J. Pantta ja, and W. C. Tan. The complexity of data exchange. In Proc. of PODS 2006, pages 30--39, 2006. Google Scholar
Digital Library
- M. Lenzerini. Data integration: A theoretical perspective. In Proc. of PODS 2002, pages 233--246, 2002. Google Scholar
Digital Library
- L. Libkin. Data exchange and incomplete information. In Proc. of PODS 2006, pages 60--69, 2006. Google Scholar
Digital Library
- J. Madhavan and A. Y. Halevy. Composing mappings among data sources. In Proc. of VLDB 2003, pages 572--583, 2003. Google Scholar
Digital Library
- R. Rosati. On the decidability and finite controllability of query processing in databases with incomplete information. In Proc. of PODS 2006, pages 356--365, 2006. Google Scholar
Digital Library
- I. Tatarinov and A. Halevy. Efficient query reformulation in peer data management. In Proc. of ACM SIGMOD, 2004. Google Scholar
Digital Library
Index Terms
On reconciling data exchange, data integration, and peer data management
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