SBIR/STTR Research Award

Project Consolidate

Award identifier 571a9122b718dacd227d33dea00c9d3530791e5fcd36ec8ba43053f66df52adbAwarding agency Department of Defense · Office of the Secretary of Defense

Award amount

$249,961

Program and phase

STTR · Phase I

Award year

2022

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Award details

Awarding agency
Department of Defense
Branch
Office of the Secretary of Defense
Recipient company
APTIMA INC
Proposal award date
2022-05-16
Contract end date
2023-05-14
UEI
K1GCPNNZKEN7
Solicitation number
21.C
Topic code
OSD21C-006

Research abstract

The increasing incidence of population migration due to human-caused crises, such as wars or civil strife, or from environmental causes, such as droughts, fires, and other natural disasters, can have significant impacts on DoD interests with implications for humanitarian assistance/disaster relief (HA/DR) operations and stabilization efforts. These changing population dynamics can exacerbate already fragile states and have important security implications for United States forces involved in Civil Military Operations and Civil Affairs in the migration-affected regions. Being able to more accurately forecast and predict migration patterns—leveraging a diverse set of open-source datasets—will allow policymakers to more effectively prepare regions for change by taking into consideration the impacts on infrastructure and on human and social capital. In response to these challenges, scientific efforts across academia and the private sector have led to creation of large amounts of data relevant for understanding population migration. The sheer volume and complexity of this often unstructured and disparate information, however, make the data difficult to use without a comprehensive, flexible, and extensible modeling framework. Many of these efforts to model population dynamics are siloed, making it difficult to share insights, techniques, and datasets to facilitate rapid knowledge sharing and prototyping efforts. This makes it difficult for newly developed datasets, tools, and models to communicate across disciplines working with similar data or on similar problems. To address these problems, Aptima proposes to develop Project Consolidate, a collaborative migration modeling tool that (1) learns the context of research activities that share commonalities (e.g., regions, datasets, variables, models) and (2) utilizes innovative methods to generate recommendations to researchers. These recommendations will support rapid prototyping and facilitate more robust modeling efforts to improve research for the population migration community. Aptima is partnering with the College of William and Mary (W&M), creator of the AidData platform and GeoQuery data processing and querying technology, and Sand Hill Geographic, a leading developer of technologies in the geographic information system (GIS) domain. Project Consolidate will create innovative methods for modeling to improve collaboration on population migration modeling efforts. It will also increase the cadence of predictive research analyses to more accurately predict population migration impacts. The Project Consolidate system will accomplish these goals by (1) reducing data processing barriers for analyses through GeoQuery, (2) intelligently tagging the contents to support archiving and querying capabilities, (3) facilitating predictive modeling and transparency, and (4) increasing collaboration between researchers through recommendations of relevant content and other users.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

520 SBIR/STTR records share this UEI (1997–2025). Reported award amounts total $208,057,185. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense, National Aeronautics and Space Administration, Department of Health and Human Services, Department of Transportation, Department of Energy, Department of Homeland Security

Agency intelligence

Department of Defense

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