Automated Data Transformations for Net-Centric Operations
The ever increasing number of web data sources and the additional complexity of sharing data among databases creates a growing need for less labor intensive schema matching and translation techniques. Securboration, teaming with Dr. Jens Pohl, Professor of Architecture and Executive Director of the Collaborative Agent Design Research at California Polytechnic State University, and Chairmen of the Board of CDM Technologies, is pleased to propose the Semantic Ontology-Assisted Matching System, or SOAMS, directed at data transformation solutions. As a part of our approach, the Securboration Team offers the following: (1) Highly-qualified Team with extensive experience in semantic interoperability, ontological reasoning, agent frameworks, schema matching, data transformation, and data cleansing technologies. (2) Direct alignment to Government application applied to USTRANSCOM"s Joint Deployment and Distribution Enterprise (JDDE), as indicated by the Support letters from USTRANSCOM in Section 5 of this proposal (3) Viable commercialization opportunity by integrating SOAMS technology directly into CDM"s MARVEL AES commercial release. Our approach uses a domain model that facilitates a top-down approach to the matching and translation problem by allowing schema alignment based on meaning to semantically match schema and then use syntactical methods for further matching and transformation. BENEFIT: Our partnership with Dr. Pohl and CDM will enable SOAMS to be developed with an eye towards integration possibilities with CDM"s MARVEL AES commercial product. The synergies are excellent between the two, which is a basis for the long term teaming arrangements. Additionally, SOAMS has broad capability to support SOA component vendors, particularly as a product that facilitates SOA implementations. This is important as many SOA contracts are now service-level contracts (vs. one shot commercial products) that include deployment and installation and a product such as SOAMS will enable more rapid implementation of an SOA by mitigating the labor intensive process of matching and translation.
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