How Dirty Is Your Relational Database? An Axiomatic Approach

  • Maria Vanina Martinez
  • Andrea Pugliese
  • Gerardo I. Simari
  • V. S. Subrahmanian
  • Henri Prade
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4724)


There has been a significant amount of interest in recent years on how to reason about inconsistent knowledge bases. However, with the exception of three papers by Lozinskii, Hunter and Konieczny and by Grant and Hunter, there has been almost no work on characterizing the degree of dirtiness of a database. One can conceive of many reasonable ways of characterizing how dirty a database is. Rather than choose one of many possible measures, we present a set of axioms that any dirtiness measure must satisfy. We then present several plausible candidate dirtiness measures from the literature (including those of Hunter-Konieczny and Grant-Hunter) and identify which of these satisfy our axioms and which do not. Moreover, we define a new dirtiness measure which satisfies all of our axioms.


Relational Database Functional Dependency Integrity Constraint Axiomatic Approach Reliable Attribute 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Maria Vanina Martinez
    • 1
  • Andrea Pugliese
    • 2
  • Gerardo I. Simari
    • 1
  • V. S. Subrahmanian
    • 1
  • Henri Prade
    • 3
  1. 1.University of MarylandCollege ParkUSA
  2. 2.University of CalabriaRendeItaly
  3. 3.IRITToulouseFrance

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