
"But software evolves. Most open-source software used in research is refined both iteratively and collectively, and has no published 'version of record'. Updates can target various versions and releases, meaning that each aspect of the software - the project as a whole, a specific version or a single file - can require a different way to refer to it. This creates confusion."
"Recent efforts to do this have focused on adapting a set of principles initially developed to make research data findable, accessible, interoperable and reusable (FAIR). But this approach relies on tracking data, archiving them and making metadata available. For software, it would create a large administrative burden that would have to be sustained for decades. That would be disproportionately time-consuming to those who maintain and improve software - and whose efforts are already underappreciated."
"Imagine, for example, maintaining a software package that has tens of contributors (which is not rare). Each release and version requires a new upload to an archive, with updates to the metadata, author list, dependencies (any other software required for programs to run), interoperability (which other programs it can work with) and more. Some programs have a weekly or even daily release cycle, making the FAIR approach impractical."
Scientific research relies on software for experiments, data handling, visualization, instrument control and simulations across scales. Open-source research software evolves iteratively and collectively and often lacks a single published version of record. Different releases, versions and files require distinct citation methods, causing confusion. Software must be preserved to support study findings, yet also remain available, supported and improved over time, creating a double bind. Adapting FAIR data principles to software demands extensive tracking, archiving and metadata maintenance, imposing a large administrative burden that would be especially onerous for frequently updated projects with many contributors.
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