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Providing practical solutions for implementing FAIR principles throughout the lifecycle of research data is one of the main goals of the FAIRsFAIR project. This report provides an update of the FAIR assessment metrics developed by the task 4.5 team and describes in detail two practical tools for assessing the FAIRness of research data during data acquisition, and for data already archived in a trusted data repository. The tools are named FAIR-Aware, and F-UJI. The report also presents a badging scheme for visualising and sharing the FAIR level of individual datasets.
FAIR Data, FAIR Principles, EOSC, Trustworthy Digital Repository, metadata, CoreTrustSeal, data identifier, FAIRness Assessment Tools, FAIR
FAIR Data, FAIR Principles, EOSC, Trustworthy Digital Repository, metadata, CoreTrustSeal, data identifier, FAIRness Assessment Tools, FAIR
| 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). | 0 | |
| 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. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 61 | |
| downloads | 61 |

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