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Presentation . 2026
License: CC BY
Data sources: Datacite
ZENODO
Presentation . 2026
License: CC BY
Data sources: Datacite
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Developing Actionable Guidelines for FAIR Research Software

Authors: Struck, Alexander;

Developing Actionable Guidelines for FAIR Research Software

Abstract

Abstract: Research software plays a fundamental role in modern scholarly research. Ensuring that this software is Findable, Accessible, Interoperable, and Reusable (FAIR) is essential for enabling reproducibility, enhancing transparency, safeguarding sustainability, and driving scientific progress. The FAIR Principles for Research Software (FAIR4RS Principles) were established in 2022 through an international collaborative effort to provide a general framework for making software FAIR [10.15497/RDA00068]. Similar to the FAIR Principles for Scientific Data, the FAIR4RS Principles remain aspirational by design and do not provide details for their concrete implementation. The FAIR Biomedical Research Software (FAIR-BioRS) Guidelines were created in 2023 to provide actionable instructions for making biomedical research software compliant with the FAIR4RS Principles [10.1038/s41597-023-02463-x]. Although most elements of the FAIR-BioRS guidelines are not specific to biomedical research software, and community feedback suggested they be generalized to all research software, such generalization needs further cross-disciplinary input. Domain-agnostic guidelines would support research software engineers in aligning their software with the FAIR4RS Principles, as evidenced by the FAIR4RS review survey [10.5281/zenodo.15381365]. Acting on this need, authors of the FAIR-BioRS guidelines initiated the Task Force “Actionable Guidelines for the FAIR Research Software (Actionable FAIR4RS)” in December 2024 under the Research Software Alliance (ReSA) [researchsoft.org/tf-actionable-fair4rs/]. The Task Force consists of a diverse international team of researchers , research software engineers and research managers from various fields, including software engineering, knowledge representation, biomedical research, and data science. The Task Force works to create and provide actionable and domain-agnostic guidelines for implementing the FAIR4RS Principles, through a comprehensive, community-driven methodology. Building on the FAIR-BioRS guidelines, the Task Force began by conducting an in-depth analysis of the FAIR4RS Principles and identified six key categories where actionable instructions were needed to comply with the principles: identifiers, metadata for software publication and discovery, standards for inputs/outputs, qualified references, metadata for reuse, and licenses. For each category, a dedicated sub-group is currently conducting literature reviews, data analyses, community outreach and discussion sessions to identify how the principles can be practically satisfied. Some of the challenges include identifying suitable identifiers, archival repositories, metadata standards, and best practices across research domains. By the time of our presentation at deRSE26, we expect the first draft of the guidelines to be ready for community review. In our presentation, we will provide an overview of the Task Force, present the draft guidelines, and outline opportunities for community involvement in shaping the guidelines further. We believe this effort aligns well with several deRSE26 conference topics, including “cross-disciplinary advancement”, “research software metadata”, “open science & collaboration”, “reproducibility”, and others. Given the progressive adoption of the FAIR4RS Principles [10.5281/ZENODO.10816032], including by funders and research organizations, we expect this presentation to provide attendees at deRSE26 with an understanding of how they can satisfy the FAIR4RS Principles for their own research software through the actionable, easy-to-follow, and easy-to-implement guidelines.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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