FAIR+S: A validation study of a framework for sustainable research data and software

2026-07-01 · Source: cs.SE updates on arXiv.org · Field: Science & Research — Research Methodology & Innovation, Environmental Science & Earth Systems, Engineering & Applied Sciences · Depth: Intermediate, extended

Summary

The FAIR+S framework extends the established FAIR principles for research data and software management (RDSM) by explicitly integrating sustainability considerations throughout the digital research artefact lifecycle. This framework addresses the current gap where FAIR principles do not account for environmental impacts like energy consumption and carbon emissions from production, execution, and maintenance. FAIR+S introduces five core principles (S1-S5) promoting energy efficiency attributes, sustainability benchmarks, alignment with existing frameworks (e.g., ISO/IEC 21031:2024, GHG Protocol), carbon transparency and accountability, and life cycle sustainability. A validation study, involving a structured expert survey with 27 qualified participants, assessed the framework's relevance, feasibility, and perceived value. Results indicate broad conceptual support, with principles rated moderately to very important (e.g., S1 M=4.0, S5 M=3.2), and a strong perception of added value, including 85.7% of experts believing lifecycle sustainability statements improve trust. However, significant implementation challenges remain, primarily due to a lack of standardized tools, clear guidance, and sufficient expertise.

Key takeaway

For research scientists and software engineers developing or managing digital research artefacts, FAIR+S provides a validated framework to integrate environmental sustainability. You should advocate for institutional support, including standardized tools and training, to overcome current implementation barriers. Policy makers should consider mandating FAIR+S-aligned reporting to foster transparency and accountability, ensuring long-term trust and comparability in research outputs.

Key insights

FAIR+S integrates sustainability into research data and software management, addressing environmental impacts.

Principles

• Sustainability must be explicit in RDSM.
• Transparency and accountability build trust.
• Standardized tools drive adoption.

Method

A structured expert survey, grounded in Design Science Research, assessed FAIR+S relevance, feasibility, and value using mixed-methods analysis of quantitative and qualitative data from 27 experts.

In practice

• Report energy efficiency attributes and lifecycle sustainability.
• Utilize community-accepted benchmarks and align with ISO/GHG frameworks.
• Disclose carbon measurement methods and assumptions.

Topics

• FAIR+S Framework
• Research Data Management
• Software Sustainability
• Environmental Accountability
• Carbon Emissions
• Expert Validation

Code references

• ellariel/fairs-pilot-validation

Best for: AI Scientist, Research Scientist, Software Engineer, Policy Maker

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Editorial summary, takeaway, and curation by AIssential. Original article published by cs.SE updates on arXiv.org.