Computational workflows have recently emerged as an effective paradigm to manage large-scale distributed scientific computations. Workflow systems can automate many execution-level details and provide assistance in composing and validating workflows. However, there is still a significant effort involved in creating these workflows since they often represent collaborative and exploratory science experiments. Therefore, current practice is effective in producing results but not cost-effective for widespread adoption. Drawing from our previous research in computational workflows across scientific disciplines, this paper analyzes the tasks and overall process for designing these workflows. We discuss software engineering methodologies and their relevance to creating workflows as a unique kind of software artifact. We also discuss our ongoing work to make workflow applications more cost effective and lower the barriers for widespread adoption of workflow technologies.
['Yolanda Gil', 'Pedro A. González-Calero', 'Ewa Deelman']
On the black art of designing computational workflows