Communicating with Pictorial Databases

  • Arturo Pizano
  • Alfonso Cardenas
  • Allen Klinger
Part of the Languages and Information Systems book series (LISS)


This chapter presents a model and a language for specifying spatial queries: predicates involving the position on objects in a database picture. For example, “hospitals located within ten miles of a given school,” “cities adjacent to Los Angeles,” or “streets that intersect Highway 10 in downtown LA.” Most existing pictorial query languages are text oriented, e.g., GRAIN,(2) IDMS, PSQL,(11) MIM,(13) and PROBE.(10) Others such as qpe(3) and PICQUERY,(9) follow the query-by-example approach (insertion of example values in tables), but do not make use of the visual properties of pictorial data. The language presented here differs from these methods by using pictures for specifying queries. These pictures, termed query pictures, visually depict conditions to be satisfied by the results of a query. For instance, Fig. la sketches a street intersection in which the condition “automobiles and people simultaneously entering a crosswalk” is satisfied. We enable new interaction mechanisms built upon the use of visual structures to manipulate spatially related objects. The work is related to visual programming languages as defined in Ref. 4. The following discussion addresses the problem of translating query pictures into first-order predicate calculus expressions describing queries. These expressions may be used by a query-processing mechanism to identify database pictures satisfying the desired conditions.


Traffic Light State Highway Spatial Query Street Intersection Language Extension 
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.
    D. Badal, Visual recall query language, Hewlett-Packard Laboratories, Technical report No. STL-87-R, 1987.Google Scholar
  2. 2.
    S.K. Chang, N. Donato, B.H. Mc Cormigk, J. Reuss, and R. Rochetti, A relational database system for pictures, Proc. IEEE Workshop on Picture Data Description and Management, 1987, pp. 142–149.Google Scholar
  3. 3.
    N.S. Chang and K.S. Fu, Query-by-pictorial-example, IEEE Trans. Software Eng.6, 519–524, 1980.CrossRefGoogle Scholar
  4. 4.
    S.K. Chang, Visual languages: A tutorial and survey, IEEE Software4, 29–39, 1987.CrossRefGoogle Scholar
  5. 5.
    P. Chen, The entity—relationship model; towards a unified view of data, ACM Trans. Database Syst.1, 9–36, 1976.CrossRefGoogle Scholar
  6. 6.
    E.F. Codd, A relational model of data for large shared data banks, Commun. ACM13, 377–387, 1970.CrossRefGoogle Scholar
  7. 7.
    U. Dayal and H.Y. Hwang, View definition and generalization for database integration in a multibase system, IEEE Trans. Software Eng.10, 628–644, 1984.CrossRefGoogle Scholar
  8. 8.
    R. Hull and R. King, Semantic database modeling: Survey, applications and research issues, USC Computer Science Department Technical Report No. TR-86–201, 1986.Google Scholar
  9. 9.
    T. Joseph and A. Cardenas, PICQUERY: A high level query language for pictorial database management, IEEE Trans. Software Eng.14, 639–650, 1988.CrossRefGoogle Scholar
  10. 10.
    J.A. Orenstein and F.A. Manola, PROBE spatial data modeling and query processing in an image database application, IEEE Trans. Software Eng.14, 611–629, 1988.CrossRefGoogle Scholar
  11. 11.
    N. Roussopoulos, et al., An efficient pictorial database system for PSQL, IEEE Trans. Software Eng.14, 630–638, 1988.CrossRefGoogle Scholar
  12. 12.
    J.M. Smith and D.C.P. Smith, Database abstractions: Aggregation and generalization, ACM Trans. Database Syst.2, 105–133, 1977.CrossRefGoogle Scholar
  13. 13.
    D. Woelk and W. Kim, Multimedia information management in an object oriented database system, Proceedings of the 13th VLDB Conference, 1987.Google Scholar
  14. 14.
    A. Yamamoto and M. Takagi, Extraction of object features from image and its application to image retrieval, Proceedings of the 9th ICPR, IEEE, 1988, pp. 988–991.Google Scholar
  15. 15.
    G.Y. Tang, A Logical Data Organization for Integrated Databases of Pictures and Alphanumeric Data, Proc. IEEE Picture Data Description and Management Workshop, 1980, pp. 158–166.Google Scholar

Copyright information

© Plenum Press, New York 1991

Authors and Affiliations

  • Arturo Pizano
    • 1
  • Alfonso Cardenas
    • 1
  • Allen Klinger
    • 1
  1. 1.Computer Science DepartmentUniversity of CaliforniaLos AngelesUSA

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