Sharing interoperable workflow provenance: A review of best practices and their practical application in CWLProv.

ABSTRACT:

Background

The automation of data analysis in the form of scientific workflows has become a widely adopted practice in many fields of research. Computationally driven data-intensive experiments using workflows enable automation, scaling, adaptation, and provenance support. However, there are still several challenges associated with the effective sharing, publication, and reproducibility of such workflows due to the incomplete capture of provenance and lack of interoperability between different technical (software) platforms.

Results

Based on best-practice recommendations identified from the literature on workflow design, sharing, and publishing, we define a hierarchical provenance framework to achieve uniformity in provenance and support comprehensive and fully re-executable

SUBMITTER: Khan FZ 

PROVIDER: S-EPMC6824458 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature