Recording provenance of workflow runs with RO-Crate
CoRR(2023)
摘要
Recording the provenance of scientific computation results is key to the
support of traceability, reproducibility and quality assessment of data
products. Several data models have been explored to address this need,
providing representations of workflow plans and their executions as well as
means of packaging the resulting information for archiving and sharing.
However, existing approaches tend to lack interoperable adoption across
workflow management systems. In this work we present Workflow Run RO-Crate, an
extension of RO-Crate (Research Object Crate) and Schema.org to capture the
provenance of the execution of computational workflows at different levels of
granularity and bundle together all their associated products (inputs, outputs,
code, etc.). The model is supported by a diverse, open community that runs
regular meetings, discussing development, maintenance and adoption aspects.
Workflow Run RO-Crate is already implemented by several workflow management
systems, allowing interoperable comparisons between workflow runs from
heterogeneous systems. We describe the model, its alignment to standards such
as W3C PROV, and its implementation in six workflow systems. Finally, we
illustrate the application of Workflow Run RO-Crate in two use cases of machine
learning in the digital image analysis domain.
A corresponding RO-Crate for this article is at
https://w3id.org/ro/doi/10.5281/zenodo.10368989
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