Applying the FAIR Principles to computational workflows. Wilkinson, S. R., Aloqalaa, M., Belhajjame, K., Crusoe, M. R., de Paula Kinoshita, B., Gadelha, L., Garijo, D., Gustafsson, O. J. R., Juty, N., Kanwal, S., Khan, F. Z., Köster, J., Peters-von Gehlen, K., Pouchard, L., Rannow, R. K., Soiland-Reyes, S., Soranzo, N., Sufi, S., Sun, Z., Vilne, B., Wouters, M. A., Yuen, D., & Goble, C. Scientific Data, 12(1):328, February, 2025. Publisher: Nature Publishing Group![Applying the FAIR Principles to computational workflows [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex 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.
@article{wilkinson_applying_2025,
title = {Applying the {FAIR} {Principles} to computational workflows},
volume = {12},
copyright = {2025 UT-Battelle, LLC and the Authors 2025},
issn = {2052-4463},
url = {https://www.nature.com/articles/s41597-025-04451-9},
doi = {10.1038/s41597-025-04451-9},
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.},
language = {en},
number = {1},
urldate = {2025-05-21},
journal = {Scientific Data},
author = {Wilkinson, Sean R. and Aloqalaa, Meznah and Belhajjame, Khalid and Crusoe, Michael R. and de Paula Kinoshita, Bruno and Gadelha, Luiz and Garijo, Daniel and Gustafsson, Ove Johan Ragnar and Juty, Nick and Kanwal, Sehrish and Khan, Farah Zaib and Köster, Johannes and Peters-von Gehlen, Karsten and Pouchard, Line and Rannow, Randy K. and Soiland-Reyes, Stian and Soranzo, Nicola and Sufi, Shoaib and Sun, Ziheng and Vilne, Baiba and Wouters, Merridee A. and Yuen, Denis and Goble, Carole},
month = feb,
year = {2025},
note = {Publisher: Nature Publishing Group},
keywords = {Computational biology and bioinformatics, Mathematics and computing, Scientific community},
pages = {328},
}
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