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A Framework for Spatio-Multidimensional Analysis Improved by Chorems: Application to Agricultural Data

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Data Management Technologies and Applications (DATA 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 584))

Abstract

Spatial OLAP (SOLAP) systems are decision-support systems for the analysis of huge volumes of spatial data. Usually, SOLAP clients provide decision-makers with a set of graphical, tabular and cartographic displays to visualize warehoused spatial data. Geovisualization methods coupled with existing SOLAP systems are limited to interactive (multi) maps. However, a new kind of geovisualization method recently appears to provide summaries of geographic phenomena: the chorem-based methods. A chorem is theoretically defined as a schematized spatial representation, which eliminates any unnecessary details to the map comprehension. Therefore, in this paper we investigate the opportunity to integrate SOLAP and chorem systems in a unique decision-support system. We propose the ChoremOLAP system that enriches SOLAP maps with chorems. We apply our proposal to agricultural data analysis, since both chorems and SOLAP have been rarely used in this application domain. Using open data provided by the FAO, we show how ChoremOLAP is well adapted in the agricultural context.

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Author information

Authors and Affiliations

  1. INRA, UMR Métafort, Aubiere, France

    François Johany

  2. Irstea, TSCF, Aubiere, France

    Sandro Bimonte

Authors
  1. François Johany
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  2. Sandro Bimonte
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Correspondence to François Johany .

Editor information

Editors and Affiliations

  1. School of Computing, Dublin City University, Dublin, Ireland

    Markus Helfert

  2. Human-Computer Interaction, Medical University of Graz, Graz, Austria

    Andreas Holzinger

  3. Department of Informatics, University of Minho, Braga, Portugal

    Orlando Belo

  4. Dept. of Electronics and Information, Politecnico di Milano, Milan, Italy

    Chiara Francalanci

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Johany, F., Bimonte, S. (2016). A Framework for Spatio-Multidimensional Analysis Improved by Chorems: Application to Agricultural Data. In: Helfert, M., Holzinger, A., Belo, O., Francalanci, C. (eds) Data Management Technologies and Applications. DATA 2015. Communications in Computer and Information Science, vol 584. Springer, Cham. https://doi.org/10.1007/978-3-319-30162-4_5

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  • DOI: https://doi.org/10.1007/978-3-319-30162-4_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-30161-7

  • Online ISBN: 978-3-319-30162-4

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