The classification problem with semantically heterogeneous data

  • F. M. Malvestuto
  • C. Zuffada
Contributed Papers
Part of the Lecture Notes in Computer Science book series (LNCS, volume 339)


Given a database fed by two alternative data sources using a common but not identical classification criterion, if we are able to state precisely the semantical connection between the two classification systems, we can derive new and more detailed summary data. Therefore, the question whether an aggregate information is derivable or not, is fundamental to a query-processing system. We state a necessary and sufficient condition which leads to a simple procedure for deciding the answerability of a summary query and evaluating it, if answerable. Surprisingly, the condition of derivability is independent of the database instance and is dependent only on the topological properties of the graph modelling the semantical connection of the classification systems adopted.


Summary Data Statistical Database Freight Transport Derivation Problem Standard Metropolitan Statistical Area 
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.
    C. Berge, Graphs and hypergraphs. NORTH HOLLAND, 1973Google Scholar
  2. 2.
    J.A. Bondy and U.S.R. Murty, Graph theory with applications. 1976Google Scholar
  3. 3.
    C. Chen and P. Hernon, Numeric databases, Ablex Publishing Corporation, 1984Google Scholar
  4. 4.
    D. E. Denning, P. J. Denning and M. D. Schwartz, The Tracker: A Threat to Statistical Database Security, ACM Trans. on Datab. Syst. 4: 1 (1979) 76–96Google Scholar
  5. 5.
    S. Heiler and A. T. Maness, "Connecting Heterogeneous Systems and Data Sources", Working Group Notes: 2 Int. Workshop on Statistical & Scientific Database Management, in Database Engineering, 7: 1 (1984) 23–29Google Scholar
  6. 6.
    R. Johnson, "Modelling Summary Data", Proc. ACM SIGMOD 1981 Conf on "Data Management", 93–97Google Scholar
  7. 7.
    R. Johnson, "A Data Model for Integrating Statistical Interpretations", TR UCLR-86765 (1981)Google Scholar
  8. 8.
    E. L. Lawler, Combinatorial Optimization: Networks and Matroids, RINEHART & WINSTON, New York, 1976.Google Scholar
  9. 9.
    F. M. Malvestuto, "The derivation problem for summary data", Proc ACM SIGMOD 1988 Conf on "Data Management", 82–89Google Scholar
  10. 10.
    F. M. Malvestuto, M. Rafanelli, C. Zuffada, Many-source databases: some problems and solutions. IASI-CNR Tech. Rep. 218 (June 1988)Google Scholar
  11. 11.
    J. L. McCarthy et al., "The SEEDIS Project: A summary Overview of the Social, Economic, Environmental, Demographic Information System", Lawrence Berkeley Laboratory document PUB-424, April 1982Google Scholar
  12. 12.
    D. Merrill, "Problems in Spatial Data Analysis", Proc. VII SAS User Group Int. Conf., San Francisco 1982Google Scholar
  13. 13.
    Z. Michalewicz, Compromisability of a Statistical Database, Information Systems 6: 4 (1983) 301–304Google Scholar
  14. 14.
    Z. M. Ozsoyoglu and G. Ozsoyoglu, "An Extension of Relational Algebra for Summary Tables", Proc. 2 Int. Workshop on Statistical & Scientific Database Management 1983, 202–211Google Scholar
  15. 15.
    E. M. Reingold, J. Nievergelt and N. Deo, Combinatorial Algorithms: Theory and Practice. PRENTICE-HALL, 1977Google Scholar
  16. 16.
    R. Ruggles and N. Ruggles, "The Role of Microdata in the National Economic and Social Accounts", Review of Income and Wealth, June 1975, 203–216Google Scholar
  17. 17.
    H. Sato, "Handling Summary Information in a Database: Derivability", Proc. ACM SIGMOD 1981, 98–107Google Scholar
  18. 18.
    H. Sato, "Fundamental Concepts of Social/Regional Summary Data and Inferences in their Databases", Doctoral Thesis, The Faculty of Engineering, Tokyo University (1982)Google Scholar
  19. 19.
    A. Shoshani, "Statistical Databases: Characteristics, Problems and Some Solutions", Proc. VIII Int. Conf. on VERY LARGE DATA BASES (1982)Google Scholar
  20. 20.
    Ministero dell'Industria, Bilancio Energetico Nazionale. Roma, 1986Google Scholar
  21. 21.
    OECD, Energy Balance of OECD countries. Paris, 1987Google Scholar
  22. 22.
    UNITED NATIONS, "Towards a System of Social and Demographic Statistics", ST/EST/STAT/SER.F/18, New York, 1975Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1989

Authors and Affiliations

  • F. M. Malvestuto
    • 1
  • C. Zuffada
    • 1
  1. 1.STUDI-DOC, ENEARomaItaly

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