Multi-Intelligence Analytics for Next Generation Analysts (MIAGA)

Erik Blasch; Ed Waltz

doi:10.1117/12.2223993

12 May 2016 Multi-Intelligence Analytics for Next Generation Analysts (MIAGA)

Erik Blasch, Ed Waltz

Proceedings Volume 9851, Next-Generation Analyst IV; 98510M (2016) https://doi.org/10.1117/12.2223993
Event: SPIE Defense + Security, 2016, Baltimore, MD, United States

Abstract

Current analysts are inundated with large volumes of data from which extraction, exploitation, and indexing are required. A future need for next-generation analysts is an appropriate balance between machine analytics from raw data and the ability of the user to interact with information through automation. Many quantitative intelligence tools and techniques have been developed which are examined towards matching analyst opportunities with recent technical trends such as big data, access to information, and visualization. The concepts and techniques summarized are derived from discussions with real analysts, documented trends of technical developments, and methods to engage future analysts with multiintelligence services. For example, qualitative techniques should be matched against physical, cognitive, and contextual quantitative analytics for intelligence reporting. Future trends include enabling knowledge search, collaborative situational sharing, and agile support for empirical decision-making and analytical reasoning.

Citation Download Citation

Erik Blasch and Ed Waltz "Multi-Intelligence Analytics for Next Generation Analysts (MIAGA)", Proc. SPIE 9851, Next-Generation Analyst IV, 98510M (12 May 2016); https://doi.org/10.1117/12.2223993

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