2026-10-13T03:55:37Z https://www.scidb.cn/oai

10.11922/sciencedb.j00104.00071 2020-10-17T21:17:25Z

2020-10-17 FAIR Computational Workflows doi:10.11922/sciencedb.j00104.00071 en Computational workflows describe the complex multi-step methods that are used for data collection, data preparation, analytics, predictive modelling, and simulation that lead to new data products. They can inherently contribute to the FAIR data principles: by processing data according to established metadata; by creating metadata themselves during the processing of data; and by tracking and recording data provenance. These properties aid data quality assessment and contribute to secondary data usage. Moreover, workflows are digital objects in their own right. Figure 1 shows a workflow  for detecting variants  in genome sequences. The workflow  is specified  in  the Common Workflow Language, displayed using the CWL Viewer. Any CWL compliant WfMS execution engine should be able to execute  this standardized workflow description and obtain  the same  results  independent of  their underlying infrastructure, for instance using Toil executed on SLURM, or REANA on Kubernetes. Computational workflow; Reproducibility; Software; FAIR data; Provenance Carole Goble Sarah Cohen-Boulakia Stian Soiland-Reyes Daniel Garijo Yolanda Gil Michael R. Crusoe Kristian Peters Daniel Schober PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset http://www.doi.org/10.1162/dint_a_00033 Science Data Bank