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.

翻译：近年来，计算科学与数据科学领域的发展趋势表明，计算工作流作为提升生产力和可重复性的工具正日益受到认可和采纳，同时也促进了平台与处理技术的普及化。作为可共享、可发现和可重用的数字对象，计算工作流受益于FAIR原则——即可发现、可访问、可互操作和可重用。工作流社区倡议的FAIR工作流工作组（WCI-FW）是一个跨学科和跨领域的全球性开放研究开发者社区，致力于将FAIR数据与软件原则系统性地应用于计算工作流。本文提出了一系列建议并附有评述，这些评述反映了我们的讨论过程，并论证了我们的选择与调整依据。这些建议面向工作流使用者与创建者、工作流管理系统开发者以及工作流服务提供商，既可作为实施指南，也可作为讨论基础。本文提出的工作流FAIR建议将最大化其作为研究资产的价值，并促进其在更广泛社区中的采纳。