Abstract
Scientific workflows-models of computation that capture the orchestration of scientific codes to conduct in silico research-are gaining recognition as an attractive alternative to script-based orchestration. Even so, researchers developing scientific workflow technologies still face fundamental challenges, including developing the underlying science of scientific workflows. You can classify scientific-workflow environments according to three major phases of in silico research: discovery, production, and distribution. On the basis of this classification, scientists can make more-informed decisions regarding the adoption of particular workflow environments.
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