While most scientific workflows systems are based on dataflow, some amount of control-flow modeling is often necessary for engineering fault-tolerant, robust, and adaptive workflows. However, control-flow modeling within dataflow often results in workflow specifications that are hard to comprehend, reuse, and maintain. We describe new modeling constructs to address these issues that provide a structured approach for modeling control-flow within scientific workflows, and discuss their implementation within the Kepler scientific workflow system.
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