Data Translation Between Taxonomies

  • Sérgio Luis Sardi Mergen
  • Carlos Alberto Heuser
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4001)


The task of translating data from one schema into another is usually performed with the help of information stating how the elements between two schemas correspond. Translation mechanisms can use this information in order to identify how instances of a source schema must be translated. We claim that a uniform matching approach, where instances of a source classes are always translated into the same target classes, may not represent the reality, specially when the schemas involved describe taxonomies. In this paper we demonstrate taxonomies that support our idea, and propose the usage of a conditional matching approach to improve the accuracy of taxonomical instances translation.


Target Class Source Class Translation Mechanism Input Match Ontology Match 


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  1. 1.
    Abiteboul, S., Cluet, S., Milo, T.: Correspondence and translation for heterogeneous data. In: Proceedings of the 6th International Conference on Database Theory, Delphi, Greece. Springer, Berlin (1997)Google Scholar
  2. 2.
    Abiteboul, S., Cluet, S., Milo, T.: Correspondence and translation for heterogeneous data. Theor. Comput. Sci. 275(1-2), 179–213 (2002)MATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    Boyd, M., Kittivoravitkul, S., Lazanitis, C., Mçbrien, P., Rizopoulos, N.: AutoMed: A BAV data integration system for heterogeneous data sources. In: Persson, A., Stirna, J. (eds.) CAiSE 2004. LNCS, vol. 3084, pp. 82–97. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  4. 4.
    Chang, C.-C.K., García-Molina, H.: Conjunctive constraint mapping for data translation. In: Proceedings of the Third ACM International Conference on Digital Libraries, Pittsburgh, Pa. ACM Press, New York (1998)Google Scholar
  5. 5.
    Cluet, S., Delobel, C., Siméon, J., Smaga, K.: Your mediators need data conversion!, pp. 177–188 (1998)Google Scholar
  6. 6.
    Ehrig, M., Sure, Y.: Ontology mapping - an integrated approachGoogle Scholar
  7. 7.
    Embley, D.W., Xu, L., Ding, Y.: Automatic direct and indirect schema mapping: experiences and lessons learned. SIGMOD Rec. 33(4), 14–19 (2004)CrossRefGoogle Scholar
  8. 8.
    Gal, A., Anaby-Tavor, A., Trombetta, A., Montesi, D.: A framework for modeling and evaluating automatic semantic reconciliation. The VLDB Journal 14(1), 50–67 (2005)CrossRefGoogle Scholar
  9. 9.
    Giunchiglia, F., Shvaiko, P., Yatskevich, M.: S-match: an algorithm and an implementation of semantic matching. In: Kalfoglou, Y., Schorlemmer, M., Sheth, A., Staab, S., Uschold, M. (eds.) Semantic Interoperability and Integration, Dagstuhl Seminar Proceedings, Dagstuhl, Germany, vol. 04391, Internationales Begegnungs- und Forschungszentrum (IBFI), Schloss Dagstuhl, Germany (2005) Google Scholar
  10. 10.
    Heiler, S.: Semantic interoperability. ACM Comput. Surv. 27(2), 271–273 (1995)CrossRefGoogle Scholar
  11. 11.
    Kalfoglou, Y., Schorlemmer, M.: If-map: An ontology-mapping method based on information-flow theory (2003)Google Scholar
  12. 12.
    Maedche, A., Motik, B., Silva, N., Volz, R.: MAFRA – A mApping fRAmework for distributed ontologies. In: Gómez-Pérez, A., Benjamins, V.R. (eds.) EKAW 2002. LNCS, vol. 2473, pp. 235–250. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  13. 13.
    Magnani, M., Rizopoulos, N., Brien, P.M., Montesi, D.: Schema integration based on uncertain semantic mappings. In: Delcambre, L.M.L., Kop, C., Mayr, H.C., Mylopoulos, J., Pastor, Ó. (eds.) ER 2005. LNCS, vol. 3716, pp. 31–46. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  14. 14.
    Papakonstantinou, Y., García-Molina, H., Ullman, J.: Medmaker: A mediation system based on declarative specifications. In: Proceedings of the 12th International Conference on Data Engineering, New Orleans, La. (1996)Google Scholar
  15. 15.
    Prasad, S., Peng, Y., Finin, T.: A Tool For Mapping Between Two Ontologies Using Explicit Information. In: Falcone, R., Barber, S., Korba, L., Singh, M.P. (eds.) AAMAS 2002. LNCS, vol. 2631. Springer, Heidelberg (2003)Google Scholar
  16. 16.
    Rahm, E., Bernstein, P.A.: A survey of approaches to automatic schema matching. VLDB Journal: Very Large Data Bases 10(4), 334–350 (2001)MATHCrossRefGoogle Scholar
  17. 17.
    van Keulen, M., de Keijzer, A., Alink, W.: A probabilistic xml approach to data integration. In: ICDE, pp. 459–470 (2005)Google Scholar
  18. 18.
    Wiederhold, G.: Mediators in the architecture of future information systems. In: Huhns, M.N., Singh, M.P. (eds.) Readings in Agents, pp. 185–196. Morgan Kaufmann, San Francisco (1997)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Sérgio Luis Sardi Mergen
    • 1
  • Carlos Alberto Heuser
    • 1
  1. 1.Universidade Federal do Rio Grande do SulPorto AlegreBrasil

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