Making Software FAIR: A machine-assisted workflow for the research software lifecycle

TL;DR

This paper presents SoFAIR, a project developing a machine-assisted workflow to improve the discoverability, attribution, and FAIRness of research software by identifying, validating, and registering software assets with persistent identifiers.

Contribution

It introduces a novel workflow integrating machine learning and existing infrastructures to enhance the management and FAIR compliance of research software.

Findings

Development of ML-assisted identification of research software

Integration with existing repositories and tools

Enhanced registration and archival of software assets

Abstract

A key issue hindering discoverability, attribution and reusability of open research software is that its existence often remains hidden within the manuscript of research papers. For these resources to become first-class bibliographic records, they first need to be identified and subsequently registered with persistent identifiers (PIDs) to be made FAIR (Findable, Accessible, Interoperable and Reusable). To this day, much open research software fails to meet FAIR principles and software resources are mostly not explicitly linked from the manuscripts that introduced them or used them. SoFAIR is a 2-year international project (2024-2025) which proposes a solution to the above problem realised over the content available through the global network of open repositories. SoFAIR will extend the capabilities of widely used open scholarly infrastructures (CORE, Software Heritage, HAL) and tools (GROBID) operated by the consortium partners, delivering and deploying an effective solution for the management of the research software lifecycle, including: 1) ML-assisted identification of research software assets from within the manuscripts of scholarly papers, 2) validation of the identified assets by authors, 3) registration of software assets with PIDs and their archival.