Advertisement

First-Order Patterns for Information Integration

  • Mark A. Cameron
  • Kerry Taylor
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3579)

Abstract

Advanced inter-enterprise applications operate in an environment that changes rapidly as autonomous services dynamically join and leave a community of interest at will. Well-designed integrated information views simplify inter-enterprise application development by hiding details of data distribution, extraction, filter and transformation from inter-enterprise applications, thereby shielding them from unwanted environment changes. Recently, the local-centric local-as-view (LAV) approach to integrated information view specification has attracted attention because of its maintainability advantage over the traditional global-as-view (GAV) approach. This paper introduces a first-order predicate calculus mapping language that admits LAV, GAV and global-and-local-as-view (GLAV) view mapping specifications over distributed database tables and service functions. Mapping patterns that apply to a wide range of integration problems are presented in the language. A case-study inter-enterprise application is used to illustrate the patterns in action.

Keywords

Data Integration Information Integration Global Schema Recursive Mapping Mapping Language 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Lenzerini, M.: Data integration: A theoretical perspective. In: PODS, Madison, Wisconsin, pp. 233–246 (2002)Google Scholar
  2. 2.
    Cali, A., De Giacomo, G., Lenzerini, M.: Models for information integration: turning local-as-view into global-as-view. In: Proceedings of International Workshop on Foundations of Models for Information Integration (10th Workshop in the series Foundations of Models and Languages for Data and Objects) (2001)Google Scholar
  3. 3.
    Lenzerini, M.: Data integration is harder than you thought. Keynote presentation. In: Batini, C., Giunchiglia, F., Giorgini, P., Mecella, M. (eds.) CoopIS 2001. LNCS, vol. 2172, p. 22. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  4. 4.
    Cali, A., Calvanese, D., De Giacomo, G., Lenzerini, M.: On the expressive power of data integration systems. In: Spaccapietra, S., March, S.T., Kambayashi, Y. (eds.) ER 2002. LNCS, vol. 2503, p. 338. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  5. 5.
    Seligman, L., Rosenthal, A., Lehner, P., Smith, A.: Data Integration: Where Does the Time Go? Bulletin of the IEEE Computer Society Technical Committee on Data Engineering 25 (2002)Google Scholar
  6. 6.
    Cameron, M.A., Taylor, K.L., Abel, D.J.: The Internet Marketplace Template: An Architecture Template for Inter-enterprise Information Systems. In: Batini, C., Giunchiglia, F., Giorgini, P., Mecella, M. (eds.) CoopIS 2001. LNCS, vol. 2172, pp. 329–343. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  7. 7.
    Lloyd, J.W.: Foundations of Logic Programming, 2nd edn. Springer, Heidelberg (1987)zbMATHGoogle Scholar
  8. 8.
    Levy, A.Y., Suciu, D.: Deciding containment for queries with complex objects. In: Proc. of the 16th ACM SIGMOD Symposium on Principles of Database Systems, Tucson, Arizona, pp. 20–31 (1997)Google Scholar
  9. 9.
    Popa, L., Velegrakis, Y., Miller, R.J., Hernández, M.A., Fagin, R.: Translating web data. In: Proceedings of VLDB, Hong Kong SAR, China, pp. 598–609 (2002)Google Scholar
  10. 10.
    Duschka, O.M., Genesereth, M.R., Levy, A.Y.: Recursive query plans for data integration. Journal of Logic Programming 43, 49–73 (2000)zbMATHCrossRefMathSciNetGoogle Scholar
  11. 11.
    Li, C., Chang, E.Y.: Query planning with limited source capabilities. In: ICDE, pp. 401–412 (2000)Google Scholar
  12. 12.
    Fellegi, L., Sunter, A.: A Theory for Record Linkage. Journal of the American Statistical Society 64, 1183–1210 (1969)Google Scholar
  13. 13.
    Cohen, W.: Data integration using similarity joins and a word-based information representation language. ACM Transactions on Information Systems 18, 288–321 (2000)CrossRefGoogle Scholar
  14. 14.
    Elfeky, M., Verykios, V., Elmagarmid, A.: TAILOR: A Record Linkage Toolbox. In: Proc. of the 18th Int. Conf. on Data Engineering. IEEE, Los Alamitos (2002)Google Scholar
  15. 15.
    Christen, P., Churches, T., Hegland, M.: A parallel open source data linkage system. In: Dai, H., Srikant, R., Zhang, C. (eds.) PAKDD 2004. LNCS (LNAI), vol. 3056, pp. 638–647. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  16. 16.
    Koudas, N.: Amit Marathe, D.S.: Flexible string matching against large databases in practice. In: Proceedings of the 30th VLDB Conference, Toronto, Canada (2004)Google Scholar
  17. 17.
    Cameron, M.A., Taylor, K.L., Baxter, R.: Web Service Composition and Record Linking. In: Proceedings of the Workshop on Information Integration on the Web (IIWeb 2004), Toronto, Canada (2004)Google Scholar
  18. 18.
    Cali, A., Calvanese, D., De Giacomo, G., Lenzerini, M.: Accessing data integration systems through conceptual schemas. In: Kunii, H.S., Jajodia, S., Sølvberg, A. (eds.) ER 2001. LNCS, vol. 2224, p. 270. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  19. 19.
    Guo, S., Sun, W., Weiss, M.A.: Solving satisfiability and implication problems in database systems. ACM Transactions on Database Systems (TODS) 21 (1996)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Mark A. Cameron
    • 1
  • Kerry Taylor
    • 1
  1. 1.CSIRO ICT CentreCanberraAustralia

Personalised recommendations