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A Framework for Implementing a Data Science Capability in a Military Intelligence System

EasyChair Preprint no. 1938

17 pagesDate: November 11, 2019


Modern day conflicts give rise to complex problems that traditional military intelligence approaches and tools struggle to resolve. There is a need for prediction and/or forecasting in the military domain based on effective intelligence processing capabilities for pro-active measures as well as reactive responses. Intelligence processes and tools are becoming increasingly inadequate to support the decisions of commanders and other decision makers. The tsunami of data of the current age requires a system of new processing and analysis tools, with the supporting skills, to provide the intelligence required for making decisions about complex situations. The Internet of Battlefield Things (IoBT) and resulting Big Data is a reality for current and future military operations. The field of Data Science provides a foundation for processing and analytic tools, processes and skills. This paper assesses current literature on intelligence analysis and Big Data to define a framework that will guide the implementation of a Data Science Capability for modern military operations. The intelligence system is viewed from a sociotechnical system perspective to identify high-level requirements for implementation of a proposed Data Science framework for intelligence systems. The framework is derived from mapping the requirements of the traditional intelligence cycle to the various Data Science methods, tools and skills.

Keyphrases: Big Data, Data Science, Internet of Battlefield Things, Military Intelligence

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Shaun Ball and Carien Van'T Wout and Rudolph Oosthuizen},
  title = {A Framework for Implementing a Data Science Capability in a Military Intelligence System},
  howpublished = {EasyChair Preprint no. 1938},

  year = {EasyChair, 2019}}
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