France’s Open Science Strategy 2026–2033: Infrastructure, Skills and Research Practices
In September 2026, France’s Ministry of Higher Education, Research and Space published “Opening Science in France”, its Open Science Strategy for 2026–2033. The document combines long-term objectives with an initial action plan for 2026–2029. A second action plan will cover 2030–2033.
The strategy connects the openness of research outputs with the everyday organisation of research. Repositories, training, research assessment, service funding and international cooperation are treated as interdependent elements. Particular attention is given to competence centres that help researchers put open science principles into practice.
For research institutions and support professionals in Ukraine, the document offers a useful reference for developing services that connect research data management, professional support and participation in the European Open Science Cloud (EOSC).
From successive action plans to a long-term strategy
The strategy builds on France’s two previous national open science plans and established infrastructures: HAL, the national open archive for publications; Recherche Data Gouv, the research data ecosystem; Software Heritage, the source code archive; and the French Open Science Monitor.
It also acknowledges that substantial work remains. Data sharing is not yet routine across all disciplines, research software is insufficiently recognised as a scientific contribution, and open science services need more sustainable organisational and financial arrangements.
The central ambition is therefore to make open science a standard part of research practice, supported by suitable tools, professional expertise and recognition.
Eight strategic objectives
The strategy identifies four cross-cutting objectives and four objectives addressing major types of research outputs.
Eight Objectives of France’s Open Science Strategy
| Objective | Focus | Planned measures |
|---|---|---|
| Enabling conditions for open science | ||
| SO1 | Practices and skills | Recognition of open science in assessment, training, research reproducibility and guidance on the use of AI. |
| SO2 | Governance and monitoring | Policy coordination, targeted support, monitoring of practices and research on the impact of open science. |
| SO3 | Services and infrastructures | Sustainable funding, shared governance, standards, certification and measurement of service use. |
| SO4 | International engagement | A national EOSC node, international partnerships, open research information and persistent identifiers. |
| Openness and reuse of research outputs | ||
| SO5 | Scholarly publications | Open access, editorial quality, diverse funding models and preservation of full texts in HAL. |
| SO6 | Research data | Development of Recherche Data Gouv, competence centres, the repository and the catalogue; easier data deposit and discovery. |
| SO7 | Source code and software | A software catalogue, a shared development platform, an OSPO support network and archiving through Software Heritage. |
| SO8 | Clinical trials | Support for results reporting, structured presentation of results and monitoring of transparency. |
Summary based on the French Open Science Strategy 2026–2033 , pp. 44–47 and 52–69. Wording has been condensed for this overview.
This structure connects institutional change with the specific requirements of publications, data, software and clinical research.
Competence centres as part of research infrastructure
The sixth strategic objective—strengthening open and shared research data in accordance with FAIR principles—is particularly relevant to research data management competence centres.
The French approach combines three complementary components:
- A network of competence centres, providing local support, disciplinary expertise and training.
- A national trusted repository, supporting data deposit and sharing.
- A data catalogue, providing a common discovery point for data held in the national repository and trusted disciplinary repositories.
How Recherche Data Gouv Supports Research Data Management
| Researcher’s need | Component | Function and outcome |
|---|---|---|
| Prepare data for sharing | Competence centres | Local support, training and specialised disciplinary expertise help researchers apply the FAIR principles. |
| Deposit and preserve data | The national repository or a trusted disciplinary repository | Data are deposited in an appropriate repository. The national repository provides shared infrastructure for institutions, while disciplinary repositories address the specific needs of research fields. |
| Make data discoverable | The Recherche Data Gouv data catalogue | Brings together information about accessible data held in the national and trusted disciplinary repositories. Provides a common discovery point without requiring all datasets to be moved into a single repository. |
| Reduce the time needed for description and discovery | Planned AI tools | Assistance with completing deposit forms, harmonising metadata and semantic search. The strategy envisages the development and deployment of these tools. |
How the components work together: competence centres support researchers; repositories preserve data and provide access; the catalogue helps users discover datasets across repositories. Support can be provided throughout the research data lifecycle.
Interpretive summary based on the French Open Science Strategy 2026–2033 , pp. 64–65, actions SO6.A1–SO6.A2. The table presents the development priorities described in the strategy.
The strategy envisages expanding the competence centre network and developing skills that address the needs of individual disciplines. Support should therefore combine general data management principles with an understanding of specific research methods, formats and working practices.
For Ukraine, this provides a useful organisational lesson: repository development and professional support should be planned together. Storage and access services become more valuable when researchers can also obtain help with preparing, describing, licensing and reusing their data.
Connecting publications, data and software
The strategy places considerable emphasis on relationships between research outputs. It promotes persistent identifiers for publications, datasets, software, organisations and researchers, including DOI, SWHID, ROR and ORCID.
When these identifiers are connected through metadata, they help users establish which data support a publication, which software version was used and who contributed to the work. These relationships also support discovery, citation and reuse.
Research software has a dedicated strategic objective. Planned measures include a catalogue of research software, standardised metadata such as CodeMeta, a national collaborative software development platform and continued support for archiving through Software Heritage.
Connecting Research Outputs
| Entity | Identifier | What metadata links enable |
|---|---|---|
| Publication | DOI For example, a Crossref DOI |
Navigation from an article’s findings to related datasets, source code and information about its authors. |
| Dataset | DOI For example, a DataCite DOI |
References to data, their provenance, related publications and the software used to process them. |
| Source code and software | SWHID and DOI Depending on the object and archiving method |
Identification of archived source code or a software release and its relationship to data and publications. |
| Researcher | ORCID | Distinguishing researchers with similar names and connecting individuals with their research outputs. |
| Institution | ROR | Unambiguous identification of institutions and consistent links between organisations, affiliated researchers and research outputs. |
Discover → assess → reuse. Persistent identifiers provide unambiguous references to entities, while relationships between them must be recorded in metadata. Reproducing results also requires descriptions of methods, software versions, parameters and the research environment.
Explanatory summary based on the French Open Science Strategy 2026–2033 , p. 58, measure SO4.A1.M3; pp. 66–67. Examples of relationships illustrate practical applications.
The strategy also proposes a network of Open Source Programme Offices (OSPOs). These offices would provide legal, technical and strategic support for research software development, alongside training, documentation guidance and assistance with dissemination and reuse.
This approach broadens professional support to reflect the range of outputs produced by research teams. Data stewardship, software support and reproducibility are closely connected areas of work.
AI to assist data deposit, curation and discovery
The strategy links artificial intelligence to specific difficulties faced by researchers and data curators. Its action plan includes:
- Assisting with data deposit forms by analysing data management plans, research articles and README files.
- Enriching metadata and aligning descriptions with controlled vocabularies.
- Assessing the quality of dataset descriptions.
- Combining conventional search filters with semantic and multilingual discovery.
The intended outcome is to reduce the time needed to describe and deposit data while maintaining accurate and comprehensive metadata. These are planned measures, rather than evidence that every function has already been implemented.
For competence centres, this creates a practical area of work: testing tools on real datasets, comparing automated descriptions with expert assessments and developing guidance for researchers and curators.
Infrastructure, academic sovereignty and EOSC
The French strategy connects open infrastructure with the capacity of the research community to preserve its outputs, participate in governance and maintain reliable access over time.
It proposes diverse funding sources, consortium-based management, retention of highly skilled staff and support for recognised standards and certification. Sustainability is treated as an ongoing responsibility that includes technical maintenance, professional expertise and institutional cooperation.
A specific measure, SO4.A3.M1, calls for establishing a French national EOSC node. Its purpose is to bring together major French open science services, strengthen participation in EOSC and improve services for research communities.
This illustrates how European integration can build on existing national resources. For the National Academy of Sciences of Ukraine (NASU), it offers a reference for developing EOSC nodes and connecting services: researchers’ needs, service quality and the capacity to sustain operations should guide implementation.
Recognition, publishing and measurable progress
The strategy calls for open science practices to be recognised in the assessment of researchers, research support staff and institutions. Relevant contributions include open science skills, research software, data sharing and reuse, and the reporting of negative results where appropriate.
In scholarly publishing, support for open access is combined with attention to editorial quality, transparent costs and publishing models without publication fees. HAL retains a central role in providing open access to full texts and preserving French research publications.
Implementation is to be monitored through national and institutional instruments. Proposed indicators cover active service users, infrastructure use, data and software sharing, and certification. These measures help assess whether available services and policies are becoming part of research practice.
The strategy also maintains the principle “as open as possible, as closed as necessary”. Legitimate restrictions remain part of responsible research data management, alongside clear conditions for access and reuse.
Implications for NASU and its research data management support
The French strategy suggests several priorities for the Ukrainian research environment:
- Develop repositories and professional support together. Connect the development of DataverseUA with consultation, training and discipline-specific guidance.
- Support the full range of research outputs. Extend assistance to source code, protocols and descriptions of computational workflows, alongside datasets.
- Connect outputs through identifiers and metadata. Enable users to move from a publication to the data and software underlying its findings.
- Develop practical pathways to EOSC services. Use concrete research scenarios to establish how services help research teams carry out their work.
- Align support with funding and recognition. Provide resources for data management and service maintenance, and recognise the contributions of the professionals involved.
- Assess use and research benefits. Complement counts of events and deposited objects with evidence of reuse, reproducibility and new collaboration.
These are analytical implications for Ukraine, rather than measures prescribed by the French strategy. Their implementation should reflect existing infrastructure, institutional capacity and the needs of research communities.
For the NASU FAIR Data Competence Center, the most relevant feature of the French approach is the close connection between training, consultation and infrastructure. Together, these functions help researchers turn an understanding of open science into research outputs that others can discover, assess and reuse.
Source: Ministry of Higher Education, Research and Space. French Open Science Strategy. Opening Science in France (2026–2033). September 2026. DOI: 10.52949/94. Strategic objectives: pp. 44–47; action plan for 2026–2029: pp. 52–69.