# CUF-Links: Continuous and Ubiquitous FAIRness Linkages for reproducible research

arXiv: https://arxiv.org/abs/2201.08296 · HTML: https://mlsanity.com/paper/2201.08296/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Jan 2022.

## Built on by (most cited first, 1 of 1)

- [A GenAI System for Improved FAIR Independent Biological Database Integration](https://mlsanity.com/paper/2506.17934/) (2025)

## Abstract (arXiv)

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.