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As a service manager how may I assist my organisation to make research data we hold both FAIR and “as open as possible, as closed as necessary”? The FAIR Data Point is a protocol for (meta)data provision championed by GO-FAIR as a solution to this need. In this story we describe how two organisations have applied the FAIR Data Point (FDP) to provide FAIR data or metadata in two contexts. In Leiden University Medical Centre the FDP is used to make metadata about COVID patient data as open as possible in the interest of research, while the data is necessarily closed and held in a variety of different systems. By contrast, Dutch data service provider SURF is applying the FDP to improve the FAIRness of an extensive dataset repository that is openly accessible by default. Based on interviews with the lead protagonists in both organisations' FDP implementations we compare their rationales and approaches, and how they expect this FAIR-enabling technology to benefit their user communities.
Metadata, FAIR principles, Research data management, Data repository, FAIR data point
Metadata, FAIR principles, Research data management, Data repository, FAIR data point
| 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 |
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