On Uncertainty and Data-Warehouse Design

  • Panagiotis Chountas
  • Ilias Petrounias
  • Christos Vasilakis
  • Andy Tseng
  • Elia El-Darzi
  • Krassimir T. Atanassov
  • Vassilis Kodogiannis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3261)


In this paper we informally and formally defined what we mean by uncertain- ignorant information in relational databases and data warehouses. We classify proposed extensions to the relational data model that can represent and retrieve incomplete information. There are many different kinds of temporal ignorant information including information that is fuzzy, imprecise, indeterminate, indefinite, missing, partial, possible, probabilistic, unknown, uncertain, or vague. We will explore each variety of temporal ignorant information in detail with reference to database and data-warehouse design.


Data Warehouse Case Base Reasoning Versus Versus Versus Versus Versus Fact Table Temporal Uncertainty 
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 2004

Authors and Affiliations

  • Panagiotis Chountas
    • 1
  • Ilias Petrounias
    • 2
  • Christos Vasilakis
    • 1
  • Andy Tseng
    • 2
  • Elia El-Darzi
    • 1
  • Krassimir T. Atanassov
    • 3
  • Vassilis Kodogiannis
    • 1
  1. 1.Health Care Computing Group, School of Computer ScienceUniversity of WestminsterLondonUK
  2. 2.Department of ComputationUMISTManchesterUK
  3. 3.CLBMEBulgarian Academy of SciencesSofiaBulgaria

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