Big-Data and the Question of Horizontal and Vertical Intelligence: A Discussion on Disaster Management

  • Frederick BenabenEmail author
  • Aurelie Montarnal
  • Audrey Fertier
  • Sebastien Truptil
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 480)


Due to the unexpected context of disaster management (with heterogeneous and non-dedicated potential data sources), the classical Big-Data approaches within this business domain (schematically focused on data storage and pattern recognition) appear to be limited, especially when trying to get a situational level of such crises from data gathered from the field. That is why this article aims at discussing a specific vision of Big-Data for data management, in two steps: (i) analyzing this business domain to identify relevant characteristics, impacted or concerned by Big-Data, and describe the new key challenges that need to be tackled, and (ii) designing an innovative Big-Data framework dedicated to this particular business domain. After having highlighted the importance to push abstraction levels and especially data interpretation as a way to perform vertical intelligence in data analysis (instead of horizontal intelligence with usual approaches), the proposed Big-Data framework brings a layered approach according to three dimensions: gathering (data level), interpretation (information level), exploitation (knowledge level).


Big-Data Collaborative situation Data interpretation Metamodel Modeling Intelligence Disaster management 


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Copyright information

© IFIP International Federation for Information Processing 2016

Authors and Affiliations

  • Frederick Benaben
    • 1
    Email author
  • Aurelie Montarnal
    • 1
  • Audrey Fertier
    • 1
  • Sebastien Truptil
    • 1
  1. 1.Toulouse University, Mines Albi – Campus JarlardAlbiFrance

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