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RDM principles underpin several benefits that occur at all stages of the research cycle.

1. Rigorous planning of research stages. Indeed, the Data Management Plan is a crucial stage in research data management.
2. Improved data management practices. Currently, different problems exist:
   1. File content is generally poorly documented.
   2. Data theft or loss is common (loss of computer, USB key or hard drive, accidental deletions).
   3. Files get corrupted over time; software and data can become obsolete.
   4. If multiple copies exist, it is sometimes difficult to identify the right one, because file naming and organisation are often not standardised.
   5. Colleagues leave with data or without having documented it and the knowledge is lost.
   6. Lack of research practice transparency. RDM principles link data to the results they have produced and thus promote research reproducibility and transparency.
3. Access data collected by other researchers in other places. More broadly, sharing research data allows researchers to access valuable data that they do not need to collect on their own. Ultimately, research data can also be shared with civil society.
4. Controlled data sharing. We do not share everything. The RDM makes it possible to take all legal precautions, such as respecting respondent rights or industry sponsorship contracts, for example via access limitation and embargo periods, as is already the case for open access to research articles.
5. Rigorous and systematic research data citation:
   1. Research project data comprise a major output. It is therefore imperative to cite data and articles in order to credit authors for their work’s impact.
   2. Linking publications to data provides evidence for results.
   3. A unique identifier permanently establishes the citation and must be both flexible enough to meet the expectations of each research field and ‘common’ enough to apply to all of them (DOI article citations, for example).
6. Project visibility improves: we quote data when we use them.
7. Certain analyses can be performed by other researchers: data are used more frequently and the number of publications as well as researcher and funding organisation return on investment increases.
8. Some funders make it mandatory; some publishers make it a condition of publication; and most journals increasingly demand linking results to data.
9. Data storage and guaranteed access for research partners working on the same database.
10. Research transparency: allows for reproduction of results and improves research integrity (see above).
11. Creation of new research projects and new questions by pairing several databases, which makes it possible to promote new methods and test alternative hypotheses.