ArticlePloS one2024
Recording provenance of workflow runs with RO-Crate.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Fragment-level FAIRness: annotating scientific data and its provenance using data fragment selectors.Journal of integrative bioinformatics · 2026Article
- Fusion of computational and experimental provenance in RO-Crate.Journal of integrative bioinformatics · 2026Article
- Open and sustainable AI: challenges, opportunities and the road ahead in the life sciences.Nature methods · 2026Review
- Genome assemblies and annotations are not static and need support for tracking their evolution.Briefings in bioinformatics · 2026Review
- How far can you go? Extrapolating values of catalytic activity from known protein landscapes in natural and directed evolution.Chemical Society reviews · 2026Review
- Managing workflow executions with WESkit.Bioinformatics (Oxford, England) · 2026Article
- FAIR digital twins for biodiversity: enabling data, model, and workflow integration.npj biodiversity · 2026Article
- CBIcall: a configuration-driven framework for variant calling in large sequencing cohorts.Bioinformatics advances · 2026Article
- WorkflowHub: a registry for computational workflows.Scientific data · 2025Article
- Applying the FAIR Principles to computational workflows.Scientific data · 2025Article
- Datagraphy: toward a systematic approach to dataset discovery.GigaScience · 2025Article
- DLProv: a suite of provenance services for deep learning workflow analyses.PeerJ. Computer science · 2025Article
- Recording provenance of workflow runs with RO-Crate.PloS one · 2024Article
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Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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 objects (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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.