论文标题
cuf-links：可再现研究的连续和无处不在的公平链接
CUF-Links: Continuous and Ubiquitous FAIRness Linkages for reproducible research
论文作者
论文摘要
尽管在方法和工具方面进行了许多创造性的工作，但可重复性 - 重复用于获得研究结果的计算步骤的能力 - 仍然难以捉摸。造成这些困难的原因之一是，现有的捕获研究过程的工具与科学家的丰富工作实践并不十分吻合。我们在这里提倡简单的机制，这些机制可以轻松地与当前的工作实践集成，以捕获有关项目中消费或生产的每个数据产品的基本信息。我们认为，通过在时间和空间中扩展可发现，可访问，可互操作和可重复使用的（公平）数据的范围，以使创建连续且无处不在的公平链接（CUF-Link）连续的链条，从输入到输出，这些机制可以为出现的链接提供了强大的基础，以记录出出来的链接，这些链接是必不可少的研究。我们举例说明可以实现这些目标的机制，并回顾如何在实践中应用它们。
Despite much creative work on methods and tools, reproducibility -- the ability to repeat the computational steps used to obtain a research result -- remains elusive. One reason for these difficulties is that extant tools for capturing research processes do not align well with the rich working practices of scientists. We advocate here for simple mechanisms that can be integrated easily with current work practices to capture basic information about every data product consumed or produced in a project. We argue that by thus extending the scope of findable, accessible, interoperable, and reusable (FAIR) data in both time and space to enable the creation of a continuous chain of continuous and ubiquitous FAIRness linkages (CUF-Links) from inputs to outputs, such mechanisms can provide a strong foundation for documenting the provenance linkages that are essential to reproducible research. We give examples of mechanisms that can achieve these goals, and review how they have been applied in practice.
