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

The FAIR principles (Findable, Accessible, Interoperable, Reusable) have transformed research data management, but they do not address the environmental impact of creating and using research software and data, such as energy consumption, carbon emissions, and life-cycle impacts that become central to computer science and engineering-related domains. To bridge this gap FAIR+Sustainability or FAIR+S, an extension of the FAIR framework that embeds environmental accountability as a core element, was

Record details

Published: 17 June 2026
Source: arXiv
Category: Research
Topics: Transparency · Environment
Retrieved: 14 July 2026

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These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

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How to cite this record

ethics.ai (17 June 2026), “FAIR+S: A validation study of a framework for sustainable research data and software,” evidence record 846, https://ethics.ai/record/846 (originally published by arXiv).

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