The SoFAIR Project: A Machine-Assisted Leap Forward for Research Software

The modern research world relies heavily on software, yet until recently,
the lifecycle of research software has been largely treated as an afterthought.
Many scientists write tools for their own experiments, but long-term maintenance,
discoverability, and reusability remain major challenges. This is where the
SoFAIR Project steps in — a new initiative aiming to bring automation,
machine learning, and FAIR principles together to transform how scientific
software is managed.

Why SoFAIR Matters

The FAIR principles — Findable, Accessible, Interoperable, and Reusable — have
become a global gold standard for handling scientific data. But applying these
principles to software is far more complex. Research code is often scattered
across personal drives, inconsistent GitHub repositories, or paper supplements.
It may have unclear licensing, missing documentation, or no version tracking.

SoFAIR offers a new approach to this problem by creating a
machine-assisted workflow that identifies research software,
extracts key metadata, and registers it so that other researchers
can reliably discover and build upon it.

The project’s goal is not just to catalog software, but to create a
sustainable ecosystem where scientific code is treated as a first-class citizen.

The Core Innovation: Machine Assistance

What makes SoFAIR groundbreaking is its use of automated tools and machine
learning models to analyze scientific outputs. Instead of relying solely on
manual curation — which is slow and difficult to scale — SoFAIR detects
software references inside publications, repositories, and research workflows.

This automated approach helps answer key questions:

• What software was used to produce these results?
• Where is the authoritative code hosted?
• Is it licensed appropriately for reuse?
• Is there a citable and trackable identifier for it?

By improving the visibility and traceability of research software, SoFAIR
strengthens reproducibility — one of the biggest challenges in modern science.

Supporting the Full Software Lifecycle

Beyond discovery, the SoFAIR Project supports the entire software lifecycle.
This includes version tracking, metadata generation, dependency analysis,
documentation structuring, and sustainability recommendations.

For research groups, this means less time organizing code and more time
innovating. For institutions, it means better compliance with open science
standards and improved long-term archival quality.

The Impact on the Future of Research

If widely adopted, SoFAIR could fundamentally reshape how scientific software
is created, shared, and preserved. It brings greater transparency,
more accurate citation practices, and stronger incentives for maintaining high-quality code.

Most importantly, it reinforces a simple truth:
research software is infrastructure, and infrastructure deserves protection.

With SoFAIR’s machine-assisted pipeline, we move closer to a world where
research software becomes as discoverable and citable as traditional academic data.

Looking Ahead

The project is still developing, but its trajectory is clear. As more
researchers adopt FAIR-aligned workflows, and as automation improves,
SoFAIR has the potential to become a cornerstone of global open science.
Its approach blends cutting-edge tools with a deep commitment to openness,
collaboration, and reproducibility — values that form the heart of scientific progress.