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Article dans une revue

A hybrid risk-aware design method for spatial datacubes handling spatial vague data: Implementation and validation

Abstract : Spatial Data Warehouses (SDW) and Spatial OLAP (SOLAP) are well-known Business Intelligence (BI) technologies that aim to support multidimensional and online analysis of huge volumes of data with spatial reference. Spatial vagueness is one of the most neglected imperfections of spatial data. Although several works propose new adhoc models for handling spatial vagueness, their implementation in Spatial Database Management Systems (DBMS) and SDW is still in an embryonic state. In this paper, we present a new design method for SOLAP datacubes that allows handling vague spatial data analysis issues. This method relies on a risk management method applied to the potential risks of data misinterpretation and decision-makers’ tolerance levels to those risks. We also present a tool implementing our method and a validation of the method is done based on the designed datacubes schemas testing.
Mots-clés : OLAP
Type de document :
Article dans une revue
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https://hal.inrae.fr/hal-02601179
Déposant : Migration Irstea Publications <>
Soumis le : samedi 16 mai 2020 - 06:14:46
Dernière modification le : lundi 20 juillet 2020 - 13:06:06

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  • HAL Id : hal-02601179, version 1
  • IRSTEA : PUB00043932

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Citation

E. Edoh-Alove, S. Bimonte, Y. Bedard, François Pinet. A hybrid risk-aware design method for spatial datacubes handling spatial vague data: Implementation and validation. International Journal of Business Intelligence and Data Mining, Inderscience, 2014, 9 (3). ⟨hal-02601179⟩

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