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Multi-Dimensional Event Sourcing & Correlation - Publicly Available Information (PAI) (MDESC-P)

Award Information
Agency: Department of Defense
Branch: Special Operations Command
Contract: H9240522P0021
Agency Tracking Number: S22D-ST01-0039
Amount: $149,994.96
Phase: Phase I
Program: STTR
Solicitation Topic Code: SOCOM22D-ST01
Solicitation Number: 22.D
Solicitation Year: 2022
Award Year: 2022
Award Start Date (Proposal Award Date): 2022-08-16
Award End Date (Contract End Date): 2023-02-23
Small Business Information
4055 Hancock Street Suite 115
San Diego, CA 92110-5179
United States
DUNS: 004281099
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Chad Phillips
 (619) 795-2667
Business Contact
 Joretta Slack
Phone: (757) 971-0956
Research Institution
 Michael Moskal
4455 Genesee St., Suite 106
Buffalo, NY 14225-1955
United States

 (716) 204-5111
 Domestic Nonprofit Research Organization

Multi-Dimensional Event Sourcing & Correlation - Publicly Available Information (PAI) (MDESC-P) will support collection jointly across disparate PAI sources with coordinated cueing of more constrained intelligence, surveillance, target acquisition, and reconnaissance (ISTAR) sources. The primary objective for MDESC-P is to deliver a scalable and automated PAI collection management solution using an algorithmic approach to automate, prioritize, and optimize searches and correlations of information elements hidden within the ever-expanding volume of public information and data streams. MDESC-P will answer questions such as: 1. Can combinations of analyst supplied geospatial areas and keywords be used to infer a larger overarching context of their interests to drive PAI source prioritization and event discovery? 2. Can processes of interest be modeled and used to automatically search for “next events” in PAI for a temporally evolving sequence? 3. Can the larger overarching context of the analysts’ interest be used to prioritize PAI sources based on the strength of their relative relevance from each PAI source? and 4. Can meaningful RFIs be generated for non-PAI sources based on the gaps found between the analysts’ interest and the available PAI data? MDESC-P leverages previous investments made by the Department of Defense and Department of Homeland Security.

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

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