Publishing data in a data repository
Data repositories are online services for the deposition, description, storage, retrieval and dissemination of datasets. The datasets are described by metadata in such a way as to be retrievable.
When choosing a repository, several factors need to be taken into account. Firstly, it must meet the requirements of the funding body or publisher. Secondly, it must have all the characteristics needed to store FAIR data (findable, accessible, interoperable, reusable). We would also recommend opting for a certified "trusted repository" (Data Seal of Approval, ISO 16363, Trustworthy Repositories Audit & Certification (TRAC), etc.).
To find a suitable repository for your research field, you can consult several directories:
Publishing your data in a data paper
A data paper (or data article) is a peer-reviewed scientific publication whose main aim is to describe one or more datasets rather than the results of scientific research. The data described must be accessible, either as annexed files or more generally via a permalink (URL or DOI) to the data repository where they are stored. Data papers can be published in a data journal (a journal that only contains data papers) or in a traditional scientific journal (which publishes a range of articles including data papers).
Publishing a data paper is a way of informing the scientific community of the existence of a dataset that has been deposited in a data warehouse. This makes the data more easily visible and citable. It also enables the data to be described precisely, thereby opening up the potential for reuse.
Some examples of data journals:
Questions / Réponses
Where can I learn about research data management online?
The website DoRANum (research data: digital learning for management and sharing – in French) offers a series of resources for learning about managing and sharing research data. The site is divided into nine themes (issues, legal and ethical aspects, data management plan, persistent identifiers, metadata, etc.), and each theme is addressed in a variety of formats: short fact sheets, videos, quizzes, detailed documents, etc.
What is the point of drawing up a data management plan if it is not compulsory?
Drawing up a data management plan before beginning your project is a way of asking yourself the right questions and adopting best data management practices. Well-managed data are data that are easy to retrieve and reuse, described precisely by metadata, secure and permanent. If the journal you are publishing an article in asks you to deposit the accompanying data in a warehouse, you can rest assured that your metadata are already prepared and all you have to do is transfer them to the various fields. You can also easily make your data accessible and visible by publishing them in a data paper.
Is there a search engine that I can use to search for data in different repositories?
There are several data search engines:
DataMed provides access to various types of data in the biomedical field. It currently covers 76 repositories and offers a powerful advanced search.
Omics Discovery Index allows you to search for datasets in the fields of genomics, proteomics, transcriptomics and metabolomics. It also offers advanced search functions (by organism, by disease, etc.).
Elsevier DataSearch covers more diverse scientific fields. It can be used to access datasets from a more limited number of repositories but also some supplementary data.
Google Dataset Search is the least efficient. It offers a basic search and very few features.