Property covering: A powerful construct for schema derivations

  • Anastasia Analyti
  • Nicolas Spyratos
  • Panos Constantopoulos
Session 7a: Theoretical Issues in Modeling
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1331)


Covering is a well-known relationship in semantic and object-oriented models that holds when a class is the union of a collection of subclasses. Covering has been studied in the past only for entity classes. In this paper, we study covering for properties, and we introduce a new relationship, called property covering. Property covering holds when a property is the union of a collection of subproperties. Property covering allows to (i) partition a property into subproperties, (ii) express property value refinement, and (iii) express a particular form of negative information. We demonstrate that property covering is a powerful conceptual modeling mechanism, and we use it to provide a set of inference rules for schema derivations.


Inference Rule Female Flower Male Flower Property Covering Real World Object 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    A. Analyti, N. Spyratos, P. Constantopoulos, Property Covering: A Powerful Construct for Schema Derivations, Technical Report TR199, Institute of Computer Science, Foundation for Research and Technology-Hellas, June, (1997). Available from, cd tech-reports/1997, 1997. Google Scholar
  2. 2.
    S. Abiteboul, R. Hull, IFO: A Formal Semantic Database Model, ACM Transactions on Database Systems, 12(4), 525–565 (1987).Google Scholar
  3. 3.
    C. Batini, S. Ceri, S.B. Navathe, Conceptual and Logical Database Design: The Entity-Relationship Approach, Benjamin/Cummings, 1992.Google Scholar
  4. 4.
    P. Constantopoulos, M. Doerr, Component Classification in the Software Information Base, O.Nierstrasz and D.Tsichritzis (eds.), Object-Oriented Software Composition, Prentice-Hall (1995).Google Scholar
  5. 5.
    P. Constantopoulos, M. Theodorakis, Y.Tzitzikas, Developing Hypermedia Over an Information Repository, Proc. of the 2nd Workshop on Open Hypermedia Systems at Hypertext'96, (1996).Google Scholar
  6. 6.
    P. Constantopoulos, Y.Tzitzikas, Context-Driven Information Base Update, Proc. of the 8th Intern. Conference on Advanced Information Systems Engineering (CAiSE'96), 319–344 (1996).Google Scholar
  7. 7.
    M. Gogolla, U. Hohenstein, Towards a Semantic View of an Extended Entity-Relationship Model, ACM Transactions on Database Systems, 16(3), 369–416 (1991).Google Scholar
  8. 8.
    M. Lenzerini, Covering and disjointness constraints in type networks, Proc. of the 3rd IEEE Intern. Conference on Data Engineering, 1987.Google Scholar
  9. 9.
    J. Mylopoulos, A. Borgida, M. Jarke, M. Koubarakis, Telos — a Language for Representing Knowledge about Information Systems, ACM Transactions on Information Systems, 8(4), 325–362, (1990).Google Scholar
  10. 10.
    M.P. Papazoglou, Unraveling the Semantics of Conceptual Schemas, Communications of the ACM, 38(9), pp.80–94 (1995).Google Scholar
  11. 11.
    T.J. Teorey, D. Yang, J.P. Fry, A Logical Design Methodology for Relational Databases Using the Extended Entity-Relationship Model, Computing Surveys, 18(2), 197–222 (1986).Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Anastasia Analyti
    • 1
  • Nicolas Spyratos
    • 2
  • Panos Constantopoulos
    • 1
    • 3
  1. 1.FORTHInstitute of Computer ScienceHeraklion , CreteGreece
  2. 2.Universite de Paris-Sudrsay CedexFrance
  3. 3.Department of Computer ScienceUniversity of CreteHeraklionGreece

Personalised recommendations