Data Sharing
Research data sharing includes two dimensions: making data available and reusing existing data. Providing your data to other researchers increases the visibility of your research activities and may lead to new collaborations. Reusing data saves resources that would otherwise be required for producing them.
Data sharing requires, among other elements, data FAIRification (for example: use of recognized ontologies and standards, adoption of persistent identifiers (PIDs)), as well as detailed documentation and enriched metadata.
It is also essential to consider data sharing even when the data is not intended to be made public (for example: reuse of data within the laboratory, or sharing of active data within a collaborative project).
Maintaining sovereignty over your research data is also important, and sharing should ideally take place within secure environments. Dedicated collaborative workspaces exist for several types of data commonly handled within the Faculty of Medicine.
Research Data FAIRification
FAIRification for the purpose of sharing requires, among other things, the widespread adoption of recognized standards and persistent identifiers.
Standards
The disciplinary standards inventory @FacMed is organized by discipline and includes only recognized, widely used standards. Each entry includes a description of the standard, its creation date, and a link to fairsharing.org for further information.
Persistent Identifiers (PIDs)
The PID inventory @FacMed contains a list of persistent identifiers covering broad application domains (person identifiers, literature identifiers, code identifiers) as well as identifiers specific to the medical sciences (proteins, genes, lipids, antibodies, etc.).
Where to Share Research Data?
During Research
Several solutions exist for exchanging research data through collaborative workspaces. These workspaces are often specific to certain data types or disciplines. The inventory of collaborative workspaces @FacMed provides descriptions of the recommended environments for research activities within the Faculty, includes information on data sovereignty, and indicates contact persons if needed.
At the End of the Research
The ResearchData @UNIGE webpage lists commonly used generalist repositories such as Yareta, Zenodo, or OSF.
The use of disciplinary data repositories is strongly recommended for certain data types (e.g., genetic data). This significantly increases the visibility of your datasets and, consequently, your research activities. The inventory of disciplinary data repositories @FacMed compiles repositories relevant to the Faculty of Medicine.
You may use this inventory to identify the best suited repository for disseminating your research data. You may also use it to explore existing datasets in your field and identify data ready to be reused for your own research activities.
In this inventory, repositories are classified by discipline. Additional information on each repository is available via associated links to fairsharing.org or re3data.org. You can also quickly check whether repositories are recommended by the SNSF or by other funding agencies or scientific publishers.
In addition, the National Institutes of Health (NIH) provide the NIH-Supported Data Sharing Resources, an inventory of repositories supported by the NIH. The SNSF also provides a list of data repositories commonly used by the Swiss research community and meeting the SNSF’s Open Research Data (ORD) criteria.
Data Sharing Working Group
Valérie Barbié, Camilla Bellone, Eric Beuchotte, Philippe Bijlenga, Laurent Bouysset, Hugues Cazeaux, Sébastien Courvoisier, Arnaud Didierlaurent, Timothy Frayling, Aurélie Kamoun, Floriane Muller, Douglas Teodoro
Contact person:
Latest update: 2026-01-29