Sharing Data
In the context of Open Science, the final step, which aims to publish and disseminate datasets in accordance with the FAIR principles, marks the completion of the process. This step does not involve sharing all the data produced, as certain datasets, such as those containing personal data, will need to be protected. It is essential to address the issue of the legal classification of data in advance, as this determines which legal framework applies to the produced datasets.
Datasets containing data that must be protected (health data, trade and industrial secrets, etc.) can be cataloged in repositories with a detailed description of their content, without making the data itself accessible. This approach helps promote the team’s work and encourages potential collaborations while protecting the outputs that require protection.
For datasets that can be made open, the sharing stage involves making the produced datasets available by ensuring they comply with the FAIR principles, namely Findable, Accessible, Interoperable, and Reusable. Data sharing is most often accomplished by depositing the data in trusted repositories, whether discipline-specific or general-purpose. The deposited dataset is described according to a metadata standard that is typically tailored to the discipline and is assigned a persistent identifier. Finally, an open license is added to specify which forms of reuse of the dataset are permitted.