Scientific workflows are a key enabler for complex scientific computations. They capture the interdependencies between processing steps in data analysis and simulation pipelines as well as the mechanisms to execute those steps reliably and efficiently. Workflows can capture complex processes, promote sharing and reuse, and also provide provenance information necessary for the verification of scientific results and scientific reproducibility. Workflows bring the promise of lowering the barrier to using large HPC resources for the end scientist.