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Award Information
Agency: Department of Defense
Branch: Army
Contract: W15P7T-11-C-H217
Agency Tracking Number: A102-090-0035
Amount: $69,996.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: A10-090
Solicitation Number: 2010.2
Solicitation Year: 2010
Award Year: 2010
Award Start Date (Proposal Award Date): 2010-11-15
Award End Date (Contract End Date): 2011-05-15
Small Business Information
6825 Pine Street, Suite 141
Omaha, NE 68106
United States
DUNS: 949183701
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Robert Woodley
 Senior Scientist
 (573) 458-5963
Business Contact
 Stuart Aldridge
Title: Sr. VP, Res & Dev
Phone: (402) 505-7887
Research Institution

The ability to see and understand the data is critical to situational awareness. As data becomes more prevalent, the need to link causal data into actionable information becomes paramount. Analysts are faced with mountains of data, and finding that piece of relevant information is the proverbial needle in a haystack, only with dozens of haystacks. Analysis tools that facilitate identifying causal relationships across multiple data sets are sorely needed. 21st Century Systems, Inc. (21CSI) proposes Causal-View, a causal data-mining visualization tool, to address this challenge. 21CSI has experience in developing integrated information analysis tools that enable analysts, operators, etc. to discover and see data from any source. Causal-View provides causal analysis tools to fill the gaps in the causal chain. Causal-View Phase I will research multiple algorithms to provide a rich toolkit for the user. Our ongoing research and development in ISR data analysis, CBM data-mining, and reasoning under uncertainty provides a strong background for Causal-View. From our previous successes, Causal-View technology has existing avenues of transition to the warfighter where this technology is needed. Easily, with our 100% commercialization rating, 21CSI is the right company to assist the analyst and engineer alike with causal data mining.

* Information listed above is at the time of submission. *

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