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Proceedings Paper

Next generation data harmonization
Author(s): Chandler Armstrong; Ryan M. Brown; Jillian Chaves; Adam Czerniejewski; Justin Del Vecchio; Timothy K. Perkins; Ron Rudnicki; Greg Tauer
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Paper 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.

Paper Details

Date Published: 15 May 2015
PDF: 8 pages
Proc. SPIE 9499, Next-Generation Analyst III, 94990D (15 May 2015); doi: 10.1117/12.2180458
Show Author Affiliations
Chandler Armstrong, U.S. Army Corps of Engineers (United States)
Ryan M. Brown, CUBRC (United States)
Jillian Chaves, CUBRC (United States)
Adam Czerniejewski, CUBRC (United States)
Justin Del Vecchio, CUBRC (United States)
Timothy K. Perkins, U.S. Army Corps of Engineers (United States)
Ron Rudnicki, CUBRC (United States)
Greg Tauer, CUBRC (United States)


Published in SPIE Proceedings Vol. 9499:
Next-Generation Analyst III
Barbara D. Broome; Timothy P. Hanratty; David L. Hall; James Llinas, Editor(s)

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