Data Semantics Revisited

  • Alexander Borgida
  • John Mylopoulos
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3372)


The problem of data semantics is establishing and maintaining the correspondence between a data source and its intended subject matter. We review the long history of the problem in Databases, and contrast it with recent research on the Semantic Web. We then propose two new directions for research on the problem and sketch some open research questions.


Relational Database Description Logic Relational Schema Semantic Mapping Data Semantic 
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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  1. 1.
    Zelazny, R.: 24 views of Mount Fuji. Isaac Asimov’s Science Fiction Magazine 7 (1985)Google Scholar
  2. 2.
    Codd, E.: A relational model for large shared data banks. Communications of the ACM 13, 377–387 (1970)zbMATHCrossRefGoogle Scholar
  3. 3.
    Abrial, J.R.: Data semantics. In: Klimbie, K. (ed.) Data Management Systems. North-Holland, Amsterdam (1974)Google Scholar
  4. 4.
    Chen, P.: The entity-relationship model: Towards a unified view of data. In: Proc. International Conference on Very Large Databases, VLDB 1975 (1975)Google Scholar
  5. 5.
    Berners-Lee, T., Fischetti, M.: Weaving the Web: The Original Design and Ultimate Destiny of the World Wide Web by Its Inventor, Harper, San Francisco (1999)Google Scholar
  6. 6.
    Berners-Lee, T., Hendler, J., Lassila, O.: The semantic web. Scientific American (2001)Google Scholar
  7. 7.
    W3C: Web ontology language (owl) version 1.0 (2003),
  8. 8.
    Ladkin, P.: Abstraction and modeling, research report RVS-Occ-97-04, University of Bielefeld, 1997; Technical report (1997),
  9. 9.
    Levesque, H.: Foundations of a functional approach to knowledge representation. Artificial Intelligence 23 (1984)Google Scholar
  10. 10.
    Borgida, A.: Description logics in data management. IEEE Transactions on Knowledge and Data Engineering 7, 671–682 (1995)CrossRefGoogle Scholar
  11. 11.
    Reiter, R.: Towards a logical reconstruction of relational database theory. In: Brodie, M., Mylopoulos, J., Schmidt, J. (eds.) On Conceptual Modelling, pp. 191–233. Springer, Heidelberg (1984)Google Scholar
  12. 12.
    Miller, R., Haas, L., Hernadez, M.: Schema mapping as query discovery. In: Proc. International Conference on Very Large Databases (VLDB 2000), Cairo (2000)Google Scholar
  13. 13.
    Pottinger, R., Bernstein, P.: Merging models based on given correspondences. In: Proc. International Conference on Very Large Databases (VLDB 2003), Berlin, pp. 826–873 (2003)Google Scholar
  14. 14.
    Levy, A., Rajaraman, A., Ordille, J.: Querying heterogeneous information sources using source descriptions. In: Proc. International Conference on Very Large Databases (VLDB 1996), Mumbay, pp. 251–262 (1996)Google Scholar
  15. 15.
    Lenzerini, M.: Data integration: A theoretical perspective. In: Proc. International Conference on Principles of Database Systems (PODS 2002), pp. 233–246 (2002)Google Scholar
  16. 16.
    Friedman, M., Levy, A., Millstein, T.: Navigational plans for data integration. In: Proc. National Conference on Artificial Intelligence (AAAI 1999), pp. 67–73 (1999)Google Scholar
  17. 17.
    Madhavan, J., Halevy, A.: Composing mappings among data sources. In: Proc. International Conference on Very Large Databases (VLDB 2003), Berlin, pp. 572–583 (2003)Google Scholar
  18. 18.
    Fagin, R., Kolaitis, P., Popa, L., Tan, W.C.: Composing schema mappings: Second-order dependencies to the rescue. In: Proc. International Conference on Principles of Database Systems (PODS 2004), pp. 83–94 (2004)Google Scholar
  19. 19.
    Bernstein, P., Giunchiglia, F., Kementsietsidis, A., Mylopoulos, J., Serafini, L., Zaihrayeu, I.: Data management for peer-to-peer computing: A vision. In: Proc. SIGMOD WebDB Workshop, pp. 89–94 (2002)Google Scholar
  20. 20.
    Borgida, A., Serafini, L.: Distributed description logics: Assimilating information from peer sources. Journal of Data Semantics, 153–184 (2003)Google Scholar
  21. 21.
    Proceeding of semantic integration workshop, at ISWC2003, Sanibel Island, October 2003 (2003),
  22. 22.
    Smith, B.C.: The correspondence continuum, TR CSLI-87-71, Stanford University. Technical report (1987)Google Scholar
  23. 23.
    Halevy, A., Ives, Z., Suciu, D., Tatarinov, I.: Schema mediation in peer data management systems. In: Proc. International Conference on Data Engineering, ICDE 2003 (2003)Google Scholar
  24. 24.
    Buneman, P., Khanna, S., Tan, W.C.: Why and where: A characterization of data provenance. In: Proc. International Conference on Database Theory (ICDT 2001), pp. 316–330 (2001)Google Scholar
  25. 25.
    Calvanese, D., De Giacomo, G., Lenzerini, M., Nardi, D., Rosati, R.: Data integration in data warehouses. Journal of Cooperative Information Systems 10, 237–271 (2001)CrossRefGoogle Scholar
  26. 26.
    Velegrakis, Y., Miller, R., Mylopoulos, J.: Representing and querying data transformations. In: Proc. International Conference on Data Engineering, ICDE 2005 (2005) (to appear)Google Scholar
  27. 27.
    An, Y., Borgida, A., Mylopoulos, J.: Refining mappings from relational tables to ontologies. In: Proc. VLDB Workshop on the Semantic Web and Databases (SWDB 2004), Toronto (August 2004)Google Scholar
  28. 28.
    Mylopoulos, J., Bernstein, P., Wong, H.: A language facility for designing database-intensive applications. ACM Transactions on Database Systems 5, 185–207 (1980)CrossRefGoogle Scholar
  29. 29.
    Barron, J.: Dialogue and process design for interactive information systems using Taxis. In: Proc. ACM SIGOA Conference on Office Information Systems, Philadelphia, pp. 12–20 (1982)Google Scholar
  30. 30.
    Greenspan, S., Mylopoulos, J., Borgida, A.: Capturing more world knowledge in the requirements specification. In: Proc. International Conference on Software Engineering (ICSE 1982), Kyoto, pp. 225–235 (1982)Google Scholar
  31. 31.
    Yu, E.: Modeling organizations for information systems requirements engineering. In: Proc. IEEE International Symposium on Requirements Engineering (RE 1993), pp. 34–41. IEEE Computer Society Press, San Diego (1993)Google Scholar
  32. 32.
    Castro, J., Kolp, M., Mylopoulos, J.: Towards requirements-driven software development methodology: The tropos project. Information Systems 27, 365–389 (2002)zbMATHCrossRefGoogle Scholar
  33. 33.
    Dardenne, A., van Lamsweerde, A., Fickas, S.: Goal-directed requirements acquisition. Science of Computer Programming 20, 3–50 (1993)zbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Alexander Borgida
    • 1
  • John Mylopoulos
    • 2
  1. 1.Dept. of Computer ScienceRutgers UniversityUSA
  2. 2.Dept. of Computer ScienceUniversity of TorontoTorontoCanada

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