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Multidimensional Structures Dedicated to Continuous Spatiotemporal Phenomena

  • Taher Omran Ahmed
  • Maryvonne Miquel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3567)

Abstract

Multidimensional structures or hypercubes are commonly used in OLAP to store and organize data to optimize query response time. The multidimensional approach is based on the concept of facts analyzed with respect to various dimensions. Dimensions are seen as axes of analysis forming a vector space in which each cell is located by a set of coordinates. In conventional multidimensional structures, dimensions have discrete values and are organized in different levels of hierarchies. However, when analysing natural phenomena like meteorology or pollution the discrete structures are not adequate. We will introduce mechanisms, based on interpolation, to spatial and temporal dimensions which will give the user the impression of navigating in a continuous hypercube. In this paper we go over the research issues associated with continuous multidimensional structures, we give some of their potentials and we propose a multidimensional model and some operations used for an OLAP of field-based data.

Keywords

Interpolation Function Data Warehouse Dimension Level Continuous Dimension Aggregation Function 
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 2005

Authors and Affiliations

  • Taher Omran Ahmed
    • 1
  • Maryvonne Miquel
    • 1
  1. 1.LIRIS – INSA de Lyon, Bât. Blaise Pascal 501.302VilleurbanneFrance

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