Journal article

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

Farah Zaib Khan, Stian Soiland-Reyes, Richard O Sinnott, Andrew Lonie, Carole Goble, Michael R Crusoe

GigaScience | BioMed Central | Published : 2019

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 framewor..

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Grants

Awarded by BioExcel CoE - European Commission Horizon 2020 Framework Programme


Awarded by European Commission's Horizon 2020 research and innovation programme


Funding Acknowledgements

F.Z.K. is funded by Melbourne International Research Scholarship (MIRS) and Melbourne International Fee Remission Scholarship (MIFRS). S.S.R. and C.G. are funded by BioExcel CoE, a project funded by the European Commission Horizon 2020 Framework Programme under contracts H2020-INFRAEDI-022018-823830 and H2020-EINFRA-2015-1-675728, aswell as IBISBA (H2020-INFRAIA-1-2014-2015-730976). MRC has received funding from the European Commission's Horizon 2020 research and innovation programme under the Grant Agreement no 739563.