Abstract
Flexibility and adaptability are regarded as the important challenges of scientific workflows. In this paper, we propose a flexible scientific workflow system using a rule-based semantic multi-agent system to handle failures, exceptions, and dynamic changes. The approach provides advantages such as making decisions at runtime, collaboration between organizations, provenance, result explanation, etc.
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