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Scientific workflows play an important role in today's science. Many disciplines rely on workflow technologies to orchestrate the execution of thousands of computational tasks. Much research to-date focuses on efficient, scalable, and robust workflow execution, especially in distributed environments. However, many challenges remain in the area of data management related to workflow creation, execution, and result management. In this paper we examine some of these issues in the context of the entire workflow lifecycle.