Assessment of FAIR

Checklist for assessment of FAIRness of your data by LCRDM (NL)

FAIR

Explanation of the FAIR principles and understand that FAIR is not the same as Open by UKSG (UK)

FAIR

FAIR recommendations by Fairsharing.org

FAIR

Fostering FAIR Data Practices by FAIRSFAIR

FAIR

Top 10 FAIR data & Software, how different disciplines implement FAIR at a different pace by Library Carpentry

FAIR

The FAIR principles to understand the importance of metadata by GO FAIR

FAIR

Concrete recommendations in Turning FAIR into reality Directive on FAIR open data by EC

FAIR

Five recommendations for FAIR software

FAIR

TOP 10 FAIR things of the Library Carpentry (building software and data skills within library and information-related communities)

FAIR

Six Recommendations for Implementation of FAIR Practice by the FAIR in Practice Task Force of the European Open Science Cloud FAIR Working Group

FAIR

FAIR-Aware is an disciplinary-agnostic online tool for the self-assessment of the FAIRness of your dataset(s)

FAIR

Do I-pass for FAIR: Self-assessment tool for organisations to evaluate their FAIR-enablingness

File formats

Preferred file formats by archives, explained by Essentials 4 Data Support

Publishing Reproducible Research Outputs

The Art of Publishing Reproducible Research Outputs, report from Knowledge Exchange

Research software

Top 10 to Improve FAIRness of research software in Library Carpentry

Research software

This LCRDM report presents a survey of current research software practices and provides recommendations

Training materials

Good Enough Research Data Management – A Very Brief Guide (University of Colombia)