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Using an Ordered Key Attribute in Database Design

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Database and Expert Systems Applications (DEXA 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1873))

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Abstract

Recently, we have extended the relational data model to incorporate linear orderings into data domains [8], which we call the ordered relational model. We herein formally define Ordered Functional Dependencies (OFDs) and Ordered INclusion Dependencies (OINDs) for the extended model. We show that the conventional sound and complete axiom systems for FDs and INDs can be generalised to the cases of OFDs and OINDs. We investigate a subclass of ordered databases, called ordered object databases, which consists of a set of ordered relations having a distinguished key attribute and enables us to view tuples as linearly ordered objects. An ordered object database possesses two desirable properties concerning OFDs and OINDs, which are useful in ordered database design. First, there is no interaction between OFDs and OINDs. Second, the implication problem for a given set of OINDs, I, whose complexity is polynomial-time in the size of I.

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Author information

Authors and Affiliations

  1. Department of Computing, Hong Kong Polytechnic University, China

    Wilfred Ng

Authors
  1. Wilfred Ng
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Editors and Affiliations

  1. Department of Computing and Mathematical Sciences, Maritime Greenwich University Campus, 30 Park Row, London, SE10 9LS, UK

    Mohamed Ibrahim

  2. University of Linz, FAW, Altenbergerstr. 69, 4040, Linz, Austria

    Josef Küng

  3. Middlesex University, Bounds Green, London, UK

    Norman Revell

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© 2000 Springer-Verlag Berlin Heidelberg

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Ng, W. (2000). Using an Ordered Key Attribute in Database Design. In: Ibrahim, M., Küng, J., Revell, N. (eds) Database and Expert Systems Applications. DEXA 2000. Lecture Notes in Computer Science, vol 1873. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44469-6_18

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  • DOI: https://doi.org/10.1007/3-540-44469-6_18

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67978-3

  • Online ISBN: 978-3-540-44469-5

  • eBook Packages: Springer Book Archive

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