Abstract
Recent trends within computational and data sciences show an increasing recognition and adoption of computational workflows as tools for productivity and reproducibility that also democratize access to platforms and processing know-how. As digital objects to be shared, discovered, and reused, computational workflows benefit from the FAIR principles, which stand for Findable, Accessible, Interoperable, and Reusable. The Workflows Community Initiative’s FAIR Workflows Working Group (WCI-FW), a global and open community of researchers and developers working with computational workflows across disciplines and domains, has systematically addressed the application of both FAIR data and software principles to computational workflows. We present recommendations with commentary that reflects our discussions and justifies our choices and adaptations. These are offered to workflow users and authors, workflow management system developers, and providers of workflow services as guidelines for adoption and fodder for discussion. The FAIR recommendations for workflows that we propose in this paper will maximize their value as research assets and facilitate their adoption by the wider community.
| Original language | English |
|---|---|
| Article number | 328 |
| Journal | Scientific Data |
| Volume | 12 |
| Issue number | 1 |
| DOIs |
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| State | Published - Dec 2025 |
Funding
This research used resources of: the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725 (SRW); Sandia National Laboratories, a multi-mission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC (NTESS), a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration (DOE/NNSA) under contract DE-NA0003525 (LP); the European Union programme Horizon Europe under grant agreements HORIZON-INFRA-2021-EOSC-01 101057388 (EuroScienceGateway), HORIZON-INFRA-2023-EOSC-01-02 101129744 (EVERSE; SS), HORIZON-INFRA-2021-EOSC-01-05 101057344 and by UK Research and Innovation (UKRI) under the UK government’s Horizon Europe funding guarantee grants 10038963 (EuroScienceGateway; CG, S-SR), 10038992 (FAIR-IMPACT; NJ); Australian BioCommons, which is enabled by NCRIS via Bioplatforms Australia funding (JG); Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) as part of GHGA - The German Human Genome-Phenome Archive (www.ghga.de, Grant Number 441914366 (NFDI 1/1)); the National Research Agency under the France 2030 program, with reference to ANR-22-PESN0007 (KB). This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). This written work is authored by an employee of NTESS. The employee, not NTESS, owns the right, title and interest in and to the written work and is responsible for its contents. Any subjective views or opinions that might be expressed in the written work do not necessarily represent the views of the U.S. Government. The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (https://www.energy.gov/doe-public-access-plan).