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Some of the shared digital artefacts of digital research are executable in the sense that they describe an automated process which generates results. One example is the computational scientific workflow which is used to conduct automated data analysis, predictions and validations. We describe preservation challenges of scientific workflows, and suggest a framework to discuss the reproducibility of workflow results. We describe curation techniques that can be used to avoid theworkflow decay'that occurs when steps of the workflow are vulnerable to external change. Our approach makes extensive use of provenance information and also considers aggregate structures called Research Objects as a means for promoting workflow preservation.