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While the benefits of scientific workflow management are widely accepted, in practice, implementing real scientific processes is a difficult task for scientists. In sharp contrast to business workflows, scientific workflow literature stops short of providing characteristic patterns that help the understanding of workflow specification and implementation. This is one of the reasons why scientific workflow management systems have not reached the same understanding as business workflow management systems by their potential users. The need for design primitives for scientific workflows has steadily increased over the years and, actually, has become more pronounced in recent years, with the employment of user-friendly scientific workflow management systems.
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