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Fusing algorithms and analysts: open-source intelligence in the age of ‘Big Data’

Research output: Contribution to journalArticle

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Fusing algorithms and analysts : open-source intelligence in the age of ‘Big Data’. / Eldridge, Christopher Alan; Hobbs, Christopher; Moran, Matthew James.

In: Intelligence and National Security, 2017.

Research output: Contribution to journalArticle

Harvard

Eldridge, CA, Hobbs, C & Moran, MJ 2017, 'Fusing algorithms and analysts: open-source intelligence in the age of ‘Big Data’', Intelligence and National Security.

APA

Eldridge, C. A., Hobbs, C., & Moran, M. J. (2017). Fusing algorithms and analysts: open-source intelligence in the age of ‘Big Data’. Intelligence and National Security.

Vancouver

Eldridge CA, Hobbs C, Moran MJ. Fusing algorithms and analysts: open-source intelligence in the age of ‘Big Data’. Intelligence and National Security. 2017.

Author

Eldridge, Christopher Alan ; Hobbs, Christopher ; Moran, Matthew James. / Fusing algorithms and analysts : open-source intelligence in the age of ‘Big Data’. In: Intelligence and National Security. 2017.

Bibtex Download

@article{3619802d9aed4d87b4904a212c596924,
title = "Fusing algorithms and analysts: open-source intelligence in the age of {\textquoteleft}Big Data{\textquoteright}",
abstract = "In the age of {\textquoteleft}Big Data{\textquoteright}, the potential value of open-source information for intelligence-related purposes is widely recognised. Of late, progress in this space has increasingly become associated with software that can expand our ability to gather, filter, interrelate and manipulate data through automated processes. The trend towards automation is both innovative and necessary. However, techno-centric efforts to replace human analysts with finely crafted algorithms across the board, from collection to synthesis and analysis of information, risk limiting the potential of OSINT rather than increasing its scope and impact. Effective OSINT systems must be carefully designed to facilitate complementarity, exploit the strengths, and mitigate the weaknesses of both human analysts and software solutions, obtaining the best contribution from both. Drawing on insights from the field of cognitive engineering, this article considers at a conceptual level how this might be achieved.",
keywords = "OSINT, Big Data, open source",
author = "Eldridge, {Christopher Alan} and Christopher Hobbs and Moran, {Matthew James}",
year = "2017",
language = "English",
journal = "Intelligence and National Security",
issn = "0268-4527",
publisher = "Routledge",

}

RIS (suitable for import to EndNote) Download

TY - JOUR

T1 - Fusing algorithms and analysts

T2 - open-source intelligence in the age of ‘Big Data’

AU - Eldridge, Christopher Alan

AU - Hobbs, Christopher

AU - Moran, Matthew James

PY - 2017

Y1 - 2017

N2 - In the age of ‘Big Data’, the potential value of open-source information for intelligence-related purposes is widely recognised. Of late, progress in this space has increasingly become associated with software that can expand our ability to gather, filter, interrelate and manipulate data through automated processes. The trend towards automation is both innovative and necessary. However, techno-centric efforts to replace human analysts with finely crafted algorithms across the board, from collection to synthesis and analysis of information, risk limiting the potential of OSINT rather than increasing its scope and impact. Effective OSINT systems must be carefully designed to facilitate complementarity, exploit the strengths, and mitigate the weaknesses of both human analysts and software solutions, obtaining the best contribution from both. Drawing on insights from the field of cognitive engineering, this article considers at a conceptual level how this might be achieved.

AB - In the age of ‘Big Data’, the potential value of open-source information for intelligence-related purposes is widely recognised. Of late, progress in this space has increasingly become associated with software that can expand our ability to gather, filter, interrelate and manipulate data through automated processes. The trend towards automation is both innovative and necessary. However, techno-centric efforts to replace human analysts with finely crafted algorithms across the board, from collection to synthesis and analysis of information, risk limiting the potential of OSINT rather than increasing its scope and impact. Effective OSINT systems must be carefully designed to facilitate complementarity, exploit the strengths, and mitigate the weaknesses of both human analysts and software solutions, obtaining the best contribution from both. Drawing on insights from the field of cognitive engineering, this article considers at a conceptual level how this might be achieved.

KW - OSINT

KW - Big Data

KW - open source

UR - http://www.tandfonline.com/doi/full/10.1080/02684527.2017.1406677

M3 - Article

JO - Intelligence and National Security

JF - Intelligence and National Security

SN - 0268-4527

ER -

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