A visual analytic framework for data fusion in investigative intelligence

Guoray Cai; Geoff Gross; James Llinas; David Hall

doi:10.1117/12.2053161

22 May 2014 A visual analytic framework for data fusion in investigative intelligence

Guoray Cai, Geoff Gross, James Llinas, David Hall

Proceedings Volume 9122, Next-Generation Analyst II; 91220A (2014) https://doi.org/10.1117/12.2053161
Event: SPIE Sensing Technology + Applications, 2014, Baltimore, MD, United States

Abstract

Intelligence analysis depends on data fusion systems to provide capabilities of detecting and tracking important objects, events, and their relationships in connection to an analytical situation. However, automated data fusion technologies are not mature enough to offer reliable and trustworthy information for situation awareness. Given the trend of increasing sophistication of data fusion algorithms and loss of transparency in data fusion process, analysts are left out of the data fusion process cycle with little to no control and confidence on the data fusion outcome. Following the recent rethinking of data fusion as human-centered process, this paper proposes a conceptual framework towards developing alternative data fusion architecture. This idea is inspired by the recent advances in our understanding of human cognitive systems, the science of visual analytics, and the latest thinking about human-centered data fusion. Our conceptual framework is supported by an analysis of the limitation of existing fully automated data fusion systems where the effectiveness of important algorithmic decisions depend on the availability of expert knowledge or the knowledge of the analyst’s mental state in an investigation. The success of this effort will result in next generation data fusion systems that can be better trusted while maintaining high throughput.

Citation Download Citation

Guoray Cai, Geoff Gross, James Llinas, and David Hall "A visual analytic framework for data fusion in investigative intelligence", Proc. SPIE 9122, Next-Generation Analyst II, 91220A (22 May 2014); https://doi.org/10.1117/12.2053161

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available