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Big Data in Civil Security Research: Methods to Visualize Data for the Geovisual Analysis of Fire Brigade Operations

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9157))

Abstract

This article gives insight in a running dissertation as well as a finished project of the Masterprogram Geoinformation and Visualization 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.

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Correspondence to Julia Gonschorek .

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© 2015 Springer International Publishing Switzerland

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Gonschorek, J. et al. (2015). Big Data in Civil Security Research: Methods to Visualize Data for the Geovisual Analysis of Fire Brigade Operations. In: Gervasi, O., et al. Computational Science and Its Applications -- ICCSA 2015. ICCSA 2015. Lecture Notes in Computer Science(), vol 9157. Springer, Cham. https://doi.org/10.1007/978-3-319-21470-2_30

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  • DOI: https://doi.org/10.1007/978-3-319-21470-2_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-21469-6

  • Online ISBN: 978-3-319-21470-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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