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Big Data in the Field of Civil Security Research: Approaches for the Visual Preprocessing of Fire Brigade Operations

Author

Listed:
  • Julia Gonschorek

    (Department of Geography, University of Potsdam, Germany)

  • Anja Langer

    (Department of Geography, University of Potsdam, Germany)

  • Benjamin Bernhardt

    (Department of Geography, University of Potsdam, Germany)

  • Caroline Räbiger

    (Department of Geography, University of Potsdam, Germany)

Abstract

This article gives insight in a running dissertation at the University in Potsdam. Point of discussion is the spatial and temporal distribution of emergencies of German fire brigades that have not sufficiently been scientifically examined. The challenge is seen in Big Data: enormous amounts of data that exist now (or can be collected in the future) and whose variables are linked to one another. These analyses and visualizations can form a basis for strategic, operational and tactical planning, as well as prevention measures. The user-centered (geo-) visualization of fire brigade data accessible to the general public is a scientific contribution to the research topic 'geovisual analytics and geographical profiling'. It may supplement antiquated methods such as the so-called pinmaps as well as the areas of engagement that are freehand constructions in GIS. Considering police work, there are already numerous scientific projects, publications, and software solutions designed to meet the specific requirements of Crime Analysis and Crime Mapping. By adapting and extending these methods and techniques, civil security research can be tailored to the needs of fire departments. In this paper, a selection of appropriate visualization methods will be presented and discussed.

Suggested Citation

  • Julia Gonschorek & Anja Langer & Benjamin Bernhardt & Caroline Räbiger, 2016. "Big Data in the Field of Civil Security Research: Approaches for the Visual Preprocessing of Fire Brigade Operations," International Journal of Agricultural and Environmental Information Systems (IJAEIS), IGI Global, vol. 7(1), pages 54-64, January.
    • Handle: RePEc:igg:jaeis0:v:7:y:2016:i:1:p:54-64
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