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(SPIDERSENSE) Situationally Pertinent Information DEtection and Relevance SENSing Engine

Award Information
Agency: Department of Defense
Branch: Defense Advanced Research Projects Agency
Contract: N6600122C4016
Agency Tracking Number: D21I-19-0261
Amount: $224,952.81
Phase: Phase I
Program: SBIR
Solicitation Topic Code: HR001121S0007-19
Solicitation Number: HR001121S0007.I
Solicitation Year: 2021
Award Year: 2022
Award Start Date (Proposal Award Date): 2022-02-24
Award End Date (Contract End Date): 2022-11-23
Small Business Information
12 Gill Street Suite 1400
Woburn, MA 01801-1111
United States
DUNS: 967259946
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Michael Keeney
 (202) 552-6118
Business Contact
 Thomas McKenna
Phone: (781) 496-2443
Research Institution

Transitioning responsibilities presents a state of risk to organizations and the success of their missions. Effective handoffs depend on adequately transferring the most mission-relevant critical knowledge, or context. Determining and prioritizing information can be difficult because it is subject to variables including work domain, current system state, tendencies of the parties involved, and scale and timeline of the handoff. To mitigate risk involved in handoffs, Aptima will develop SPIDERSENSE: Situationally Pertinent Information DEtection and Relevance SENSing Engine. In Phase I SPIDERSENSE will be a theoretical framework and application methodology that permits the identification and operationalization of the critical knowledge necessary to enable successful handoffs, thereby increasing the safety of US Warfighters and the success of their missions. Aptima will leverage a threefold approach to this framework: (1) generalized task ontology to frame the work and the transition while accounting for time and work scales; (2) structured collection and analysis of passive data streams predominantly related to the task domain to provide raw information, both documented and implied; and (3) contextualized representation of user interactions proactively collected from the system and the parties. Together these will allow for the defining, sensing, reasoning over, and delivering of human-centered context to users.

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

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