SBIR/STTR Research Award

A Dynamic Semantic Data Fabric for Integrating Master Data from Disparate Sources

Award identifier 90baa58dee63c37ceb19fd9c22f71a2d51b697e7891c7281fb11e32e60b5831eAwarding agency Department of Defense · Navy

Award amount

$139,765

Program and phase

SBIR · Phase I

Award year

2022

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Award details

Awarding agency
Department of Defense
Branch
Navy
Recipient company
FRANZ INC
Proposal award date
2022-07-11
Contract end date
2023-01-11
UEI
DASVNBV9J291
Solicitation number
22.1
Topic code
N221-077

Research abstract

The Navy needs a software solution to integrate disparate electronic sources of technical information adhering to a unified taxonomy and ontology. This solution must include tool-specific access methods that enforce conformity to the predefined ontology, either automatically or semi-automatically. Franz will apply its AI/ML techniques to develop a software solution to facilitate the data integration discussed above. The system will retrieve data from the various sources, link the data and convert to one tool-specific language, infer duplicate entities and merge into single representations, allow for two-way data flow, obfuscate data based on user/organization roles and access restrictions when required, and provide a means to traverse data across sources to understand and analyze the entire dataset. The technical objectives for this DoD Navy Phase I are to develop a concept for a Semantically Driven Data ?Integration software platform that ?Extracts key data (master data) from the various data sources (e.g., model files, applications, ?and databases) product structures and associated contents (e.g., CAD and CAM files, ?documentation, requirements, manufacturing information, service information, part/supplier ?data),? ?Maps the extracted master data to RDF semantic data according to a predefined taxonomy ??(and ontology) which enables associations between related entities across various data ?sources,? Disambiguates data entities from different data sources to eliminate duplicate entities across ?different data sources and merge into single semantic representations (URI’s),? ?Pushes “round trip” changes between data sources through certain synchronization triggers in ?the (semantic) master database,? ?Provides access control based on user’s and organization’s roles and,? ?Provides analyses on data across the entire dataset from different sources. ? Phase I efforts will articulate the functional design, algorithms, and framework required for interfacing with CSM, DOORS, and Windchill. Phase I deliverables will include detailed information regarding the software architecture and identification of a robust set of test cases that will be used to verify functionality. We will demonstrate the concept feasibility through analysis, modelling, and simulation. The Phase I ?Option will include the initial design specifications and a capabilities description to build a ?prototype solution in Phase II.? The Franz team for the Navy phase I project has over 40 years of combined experience in ?technology, specifically data science and programming. While Dr. Wu has shifted to business ?and partnership development for the company, he maintains an up-to-date knowledge in the ?state-of-the-art technology.?

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

5 SBIR/STTR records share this UEI (1991–2022). Reported award amounts total $1,088,754. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense, National Science Foundation

Agency intelligence

Department of Defense

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