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Making data FAIR but not open

appsOther research productkeyboard_double_arrow_right InteractiveResource 28 Feb 2022Publisher:ZenodoFunded by:EC | FAIRsFAIR
Authors: Molloy, Laura;

doi: 10.5281/zenodo.6302907 , 10.5281/zenodo.6302908

Making data FAIR but not open

Abstract

This implementation story discusses approaches in the data archive world towards tackling the challenges of making data as FAIR as possible, when there are compelling reasons for the data to be restricted or unavailable. This topic was included in FAIRsFAIR deliverable D3.4, Recommendations on practice to support FAIR data principles, under the theme ���Ensuring trusted curation of data���. Within that set of recommendations, the FAIRsFAIR project committed to supporting change in good practice for researchers, repositories and ethics committees on selecting and preparing sensitive data to be FAIR. This implementation story aims to support that goal.

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Keywords

FAIR principles, sensitive data, research data management, curation

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citations
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!
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