Affiliation:
1. Massachusetts Institute of Technology
2. University of Massachusetts Lowell
Abstract
We present a comprehensive classification of data misinterpretation problems and develop an approach to automatic detection and reconciliation of data interpretation conflicts in Web services composition. The approach uses a lightweight ontology augmented with modifiers, contexts, and atomic conversions between the contexts. The WSDL descriptions of Web services are annotated to establish correspondences to the ontology. Given the naive Business Process Execution Language (BPEL) specification of the desired Web services composition with data interpretation conflicts, the approach can automatically detect the conflicts and produce the corresponding mediated BPEL. Finally, we develop a prototype to validate and evaluate the approach.
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Networks and Communications
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