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Award details
- Awarding agency
- Department of Defense
- Branch
- Navy
- Recipient company
- CROWN POINT TECHNOLOGIES LLC
- Proposal award date
- 2022-07-11
- Contract end date
- 2023-10-02
- UEI
- LECJUM4A7AB1
- Solicitation number
- 22.1
- Topic code
- N221-077
Research abstract
Crown Point Technologies offers a practical approach to assist the Department of the Navy (DON) to improve data interoperability and integration of disparate data repositories across their Strategic Systems Programs (SSPs). Our proposed solution includes the design and development of a software application powered by knowledge graphs to create a dynamic "data fabric" across disparate electronic sources of technical information that supports model-based digital engineering environments. This ontology-driven approach will offer the DON the ability to maintain data consistency and integration across a host of domain-specific tools and databases, enabling advanced analytics and improved decision-making throughout the engineering design process. We will evaluate both commercial and open-source knowledge graph and data fabric technologies to develop an approach to semantically integrate targeted data sources based on the SSP’s required capabilities and preliminary requirements. This effort includes articulating functional designs, algorithms, and a framework required for interfacing with IBM Rational DOORS, Cameo Systems Modeler, and PTC Windchill. We will also deliver a detailed software architecture describing the system components, data flows, and deployment considerations. These discoveries will be used to determine the viability of the solution by ultimately developing a concept prototype.
Technology keywords
Not reported
Other awards by this recipient
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Awards with the same topic code
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Research funding history
2 SBIR/STTR records share this UEI (2022–2024). Reported award amounts total $1,139,775. Reported amounts are not federal obligations.
Phases: Phase II, Phase I
Agencies: Department of Defense
Agency intelligence
Department of Defense
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