Next generation data harmonization

Chandler Armstrong; Ryan M. Brown; Jillian Chaves; Adam Czerniejewski; Justin Del Vecchio; Timothy K. Perkins; Ron Rudnicki; Greg Tauer

doi:10.1117/12.2180458

15 May 2015 Next generation data harmonization

Chandler Armstrong, Ryan M. Brown, Jillian Chaves, Adam Czerniejewski, Justin Del Vecchio, Timothy K. Perkins, Ron Rudnicki, Greg Tauer

Author Affiliations +

Proceedings Volume 9499, Next-Generation Analyst III; 94990D (2015) https://doi.org/10.1117/12.2180458
Event: SPIE Sensing Technology + Applications, 2015, Baltimore, MD, United States

Abstract

Analysts are presented with a never ending stream of data sources. Often, subsets of data sources to solve problems are easily identified but the process to align data sets is time consuming. However, many semantic technologies do allow for fast harmonization of data to overcome these problems. These include ontologies that serve as alignment targets, visual tools and natural language processing that generate semantic graphs in terms of the ontologies, and analytics that leverage these graphs. This research reviews a developed prototype that employs all these approaches to perform analysis across disparate data sources documenting violent, extremist events.

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Chandler Armstrong, Ryan M. Brown, Jillian Chaves, Adam Czerniejewski, Justin Del Vecchio, Timothy K. Perkins, Ron Rudnicki, and Greg Tauer "Next generation data harmonization", Proc. SPIE 9499, Next-Generation Analyst III, 94990D (15 May 2015); https://doi.org/10.1117/12.2180458

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