Recherche Data Gouv and the reconceived notions about research data
Research data management raises many questions and preconceived notions within the scientific community, as highlighted in 5 preconceived notions about research data, a recent article published on the PEPR Agroecology and Digital Technology website.
Frédéric de Lamotte (INRAE, IFB), who contributed to the article, revisits each misconception to explain how the Research Data Gouv ecosystem is working to address these challenges and support researchers in applying FAIR principles.
⚠️ This article provides initial responses to common misconceptions. Please refer to the original article for full explanations.
1. I own my research data
This is not true for public research. The 2016 Digital Republic Act treats research data as public data when more than half of the work is funded by public funds...
Contribution from Recherche Data Gouv: Institutional spaces allow institutions to exercise their legal responsibility while facilitating the availability of data in accordance with FAIR principles and national sovereignty issues.
2. I can easily manage my data myself
False. Data management is a technical skill in its own right, just like statistical analysis, for example. It requires a wide range of knowledge: structuring, formats, metadata, documentation, data management plans, archiving, legal and ethical aspects, etc.
Contribution from Data Gouv Research: The ecosystem structures a comprehensive network of competence centers: data workshops and institutional reference centers for local support, thematic reference centers for disciplinary expertise, and resource centers offering guides, tutorials, and training. Researchers can thus rely on key functions related to research data, such as data stewards, data curators, etc.
3. Data management has a major environmental impact
True and false. Data management consumes energy and its impact depends on how the data is organized and stored...
Contribution from Recherche Data Gouv: The platform promotes the centralization and structuring of data, limiting unnecessary duplication. The national repository pools infrastructure and encourages good documentation practices, which prevent each researcher from keeping their own duplicate version of the same data.
4. Having the data alone is enough!
False. Without metadata, data is unusable. Metadata provides the context necessary to understand, interpret, and reuse a dataset.
Contribution from Recherche Data Gouv: The platform imposes metadata standards upon submission and provides detailed methodological guides for documentation. The Research Data College has published a checklist of actions to be taken to implement metadata management and traceability. Tutorials guide researchers step by step through the process of describing their data.
5. Implementing FAIR is too expensive and time-consuming
False. While the initial effort of documentation and structuring may sometimes seem significant, studies show that it is the absence of FAIR principles that generates the highest costs...
Contribution from Recherche Data Gouv: The ecosystem drastically reduces entry costs by offering a shared national infrastructure (trusted repository, automatic DOI assignment, metadata validation) . Free virtual classes (submitting a dataset, FAIR curation, managing a collection, etc.) quickly train teams. The referencing of disciplinary repositories guides users towards appropriate solutions, avoiding costly errors.
Key takeaway: Recherche Data Gouv transforms every preconceived notion into an opportunity: legal clarification, expert support, environmental optimization, quality assurance through metadata, and cost reduction through pooling. The ecosystem does more than just respond to challenges: it makes data management a lever for scientific performance, serving open, reproducible, and sustainable science.
Learn more about Recherche Data Gouv