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Armstrong Databases and Reasoning for Functional Dependencies and Cardinality Constraints over Partial Bags

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Part of the Lecture Notes in Computer Science book series (LNISA,volume 7153)

Abstract

Data dependencies capture meaningful information about an application domain within the target database. The theory of data dependencies is largely a theory over relations. To make data processing more efficient in practice, partial bags are permitted as database instances to accommodate partial and duplicate information. However, data dependencies interact differently over partial bags than over the idealized special case of relations. In this paper, we study the implication problem of the combined class of functional dependencies and cardinality constraints over partial bags. We establish an axiomatic and an algorithmic characterization of the implication problem. These findings have important applications in database design and data processing. Finally, we investigate structural and computational properties of Armstrong databases for the class of data dependencies under consideration. These results can be utilized to consolidate and communicate the understanding of the application domain between different stake-holders of a database.

Keywords

  • Functional Dependency
  • Data Dependency
  • Business Rule
  • Cardinality Constraint
  • Computational Property

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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Hartmann, S., Köhler, H., Link, S., Thalheim, B. (2012). Armstrong Databases and Reasoning for Functional Dependencies and Cardinality Constraints over Partial Bags. In: Lukasiewicz, T., Sali, A. (eds) Foundations of Information and Knowledge Systems. FoIKS 2012. Lecture Notes in Computer Science, vol 7153. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28472-4_10

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  • DOI: https://doi.org/10.1007/978-3-642-28472-4_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28471-7

  • Online ISBN: 978-3-642-28472-4

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