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Visual Tools and Progressive Automation for Complex Knowledge Management and Decision Support

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-19-C-0005
Agency Tracking Number: N17A-004-0108
Amount: $749,975.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: N17A-T004
Solicitation Number: 17.A
Solicitation Year: 2017
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-01-17
Award End Date (Contract End Date): 2021-01-29
Small Business Information
1650 South Amphlett Blvd. Suite 300
San Mateo, CA 94402
United States
DUNS: 608176715
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Terrance Goan
 Principal Investigator
 (206) 430-7733
Business Contact
 Nate Henke
Phone: (650) 931-2700
Research Institution
 University of Washington
 Carol Rhodes Carol Rhodes
4333 Brooklyn Avenue NE, Box 359472
Seattle, WA 98195
United States

 (206) 545-4043
 Nonprofit College or University

We propose to adapt and automate the processes and technologies associated with evidence-based decision support to the Navy—providing a tool that can synthesize current cognitive and learning science knowledge and inform decisions so as to maximize the value gained for each training expenditure. We will develop a plug-play architecture that will allow us to make the best use of emerging technologies and innovate in three ways. First, the proposed system will automatically translate aggregate evidence into a decision support environment composed of actionable visualizations and infographics. Second, we will employ artificial intelligence and machine learning to accelerate information retrieval, data extraction, and knowledge modeling—thereby allowing scientists to focus their attention on the aspects of the process where their expertise is indispensable. Third, we will design the proposed system from the start to be adaptive. End users will be able to target new information sources, change research vocabulary, and focus on new research patterns or metrics. Phase II research and development will build on the excellent progress made in Phase I and ultimately result in the successful transition of this technology.

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

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