Semantic Information Integration in the Large: Adaptability, Extensibility, and Scalability of the Context Mediation Approach
Gannon, Thomas, Madnick, Stuart E., Moulton, Allen, Siegel, Michael, Sabbouh, Marwan and Zhu, Hongwei, "Semantic Information Integration in the Large: Adaptability, Extensibility, and Scalability of the Context Mediation Approach" (May 2005). MIT Sloan Working Paper No. 4541-05; CISL Working Paper No. 2005-04. Available at SSRN:
In this paper, we identify the deficiencies of traditional approaches that address this problem using hand-coded programs or require complete data standardization. The COntext INterchange (COIN) approach overcomes these deficiencies by declaratively representing data semantics and using a mediator to create the necessary conversion programs using a small number of conversion rules. The capabilities of COIN is demonstrated using an intelligence information integration example consisting of 150 data sources, where COIN can automatically generate the over 22,000 conversion programs needed to enable semantic integration using only six parametizable conversion rules. This paper makes a unique contribution by providing a systematic evaluation of COIN and other commonly practiced approaches.
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