  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.

Software Engineering;Social and Information Networks