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Tracking Changes in Database Schemas

  • Jakub Marciniak
  • Tadeusz Pankowski
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 183)

Abstract

We discuss the problem of discovering changes in evolving XML schemas. Schema evolution is a natural, unavoidable phenomenon in contemporary data systems, that impacts both data transformation and query rewriting. We propose a rule-based algorithm that determines matched and unmatched schema elements thereby identifying changes in a schema under consideration. Additionally, we develop a method for computing edit distance in terms of some schema operations (insertion, deletion, renaming, and translocation). In result, we are able to obtain a set of operations which transform a given schema into the modified (target) form. The proposed algorithms have been fully implemented.

Keywords

Edit Distance Database Schema Edit Operation Levenshtein Distance Matching Relation 
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.

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References

  1. 1.
    Banerjee, J., Kim, W., Kim, H.J., Korth, H.F.: Semantics and implementation of schema evolution in object-oriented databases. In: SIGMOD Conference, pp. 311–322. ACM Press (1987)Google Scholar
  2. 2.
    Bex, G.J., Neven, F., den Bussche, J.V.: DTDs versus XML Schema: A Practical Study. In: WebDB, pp. 79–84 (2004)Google Scholar
  3. 3.
    Bille, P.: A survey on tree edit distance and related problems. Theor. Comput. Sci. 337(1-3), 217–239 (2005)MathSciNetzbMATHCrossRefGoogle Scholar
  4. 4.
    Chawathe, S.S., Rajaraman, A., Garcia-Molina, H., Widom, J.: Change detection in hierarchically structured information. In: Proceedings of the ACM SIGMOD International Conference on Management of Data, pp. 493–504 (1996)Google Scholar
  5. 5.
    Lerner, B.S.: A model for compound type changes encountered in schema evolution. ACM Trans. Database Syst. 25(1), 83–127 (2000)CrossRefGoogle Scholar
  6. 6.
    Marciniak, J.: XML Schema and Data Summarization. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2010. LNCS(LNAI), vol. 6114, pp. 556–565. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  7. 7.
    Marciniak, J., Pankowski, T.: Automatic xml data transformation and merging. Zeszyty Naukowe Wydzialu ETI Politechniki Gdańskiej. Technologie Informacyjne 16, 231–236 (2008)Google Scholar
  8. 8.
    Martens, W., Neven, F., Schwentick, T.: Simple off the shelf abstractions for XML schema. SIGMOD Record 36(3), 15–22 (2007)CrossRefGoogle Scholar
  9. 9.
    Navathe, S.B.: Schema analysis for database restructuring. ACM Trans. Database Syst. 5(2), 157–184 (1980)CrossRefGoogle Scholar
  10. 10.
    W3C XML Schema Definition Language (XSD) 1.1 Part 2: Datatypes (2009), www.w3.org/TR/xmlschema11-2

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Faculty of Mathematics and Computer ScienceAdam Mickiewicz UniversityPoznanPoland
  2. 2.Institute of Control and Information EngineeringPoznań University of TechnologyPoznańPoland

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