SEEK: Scalable Extraction of Enterprise Knowledge
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SEEK: Scalable Extraction of Enterprise Knowledge is a major NSF sponsored research initiative undertaken at the University of Florida.  The SEEK project involves the multi-disciplinary collaboration of faculty and students in the departments of Computer Science, Industrial Engineering, and the M.E. Rinker, Sr. School of Building Construction.

 

The purpose of the SEEK project is to enable firms of varying size and sophistication to utilize the capabilities of value-adding electronic marketplaces and decision-support tools. Why is this important and hard to accomplish today?  Currently, the firms in business networks have unique and incompatible legacy information systems.  This restricts the sharing and exchange of knowledge.

 

Incompatibility that restricts knowledge sharing is a pernicious problem. Business networks (such as supply chains) can grow very large and often are subject to changing composition as firms enter and leave the network.  As the size of the business network grows and as the sophistication in the knowledge to be shared increases, there are fewer and fewer viable solutions that enable the extraction and sharing of knowledge stored in firms’ legacy information systems.

 

SEEK is a structured approach to overcoming the knowledge extraction and sharing problem for specific business applications.  The SEEK infrastructure (currently a working prototype) provides two fundamental capabilities:

 

Rapid connection to, and privacy-constrained filtering of, a firm’s legacy data and applications with little programmatic setup; and
Ability to link source knowledge with analysis and visualization capabilities not natively available to the source.

 

These capabilities allow the rapid setup of an extended-enterprise computing infrastructure that supports improved collaboration among the firms in the business network.

 

These capabilities also represent fundamental advances in the semi-automatic sharing of information resident in heterogeneous legacy sources.  Advances in knowledge are driven by the multi-disciplinary nature of the research, where formalization of domain knowledge directs underlying data extraction and composition.  The outcome of this research provides an enabling technology for broader visions of intelligent information sharing such as those for the Semantic Web.

 

 

 

 

 

 

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