Applying the FAIR Principles to computational workflows
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arXiv
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| Autori principali: | , , , , , , , , , , , , , , , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| author | Wilkinson, Sean R. Aloqalaa, Meznah Belhajjame, Khalid Crusoe, Michael R. Kinoshita, Bruno de Paula Gadelha, Luiz Garijo, Daniel Gustafsson, Ove Johan Ragnar Juty, Nick Kanwal, Sehrish Khan, Farah Zaib Köster, Johannes Gehlen, Karsten Peters-von Pouchard, Line Rannow, Randy K. Soiland-Reyes, Stian Soranzo, Nicola Sufi, Shoaib Sun, Ziheng Vilne, Baiba Wouters, Merridee A. Yuen, Denis Goble, Carole |
| author_facet | Wilkinson, Sean R. Aloqalaa, Meznah Belhajjame, Khalid Crusoe, Michael R. Kinoshita, Bruno de Paula Gadelha, Luiz Garijo, Daniel Gustafsson, Ove Johan Ragnar Juty, Nick Kanwal, Sehrish Khan, Farah Zaib Köster, Johannes Gehlen, Karsten Peters-von Pouchard, Line Rannow, Randy K. Soiland-Reyes, Stian Soranzo, Nicola Sufi, Shoaib Sun, Ziheng Vilne, Baiba Wouters, Merridee A. Yuen, Denis Goble, Carole |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_03490 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Applying the FAIR Principles to computational workflows Wilkinson, Sean R. Aloqalaa, Meznah Belhajjame, Khalid Crusoe, Michael R. Kinoshita, Bruno de Paula Gadelha, Luiz Garijo, Daniel Gustafsson, Ove Johan Ragnar Juty, Nick Kanwal, Sehrish Khan, Farah Zaib Köster, Johannes Gehlen, Karsten Peters-von Pouchard, Line Rannow, Randy K. Soiland-Reyes, Stian Soranzo, Nicola Sufi, Shoaib Sun, Ziheng Vilne, Baiba Wouters, Merridee A. Yuen, Denis Goble, Carole Digital Libraries Software Engineering 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. |
| title | Applying the FAIR Principles to computational workflows |
| topic | Digital Libraries Software Engineering |
| url | https://arxiv.org/abs/2410.03490 |