Research Data Management

RDM Principles: A shared commitment to responsible research data practices

The University of Luxembourg promotes responsible research data management, within a research ecosystem inspired by the FAIR principles, and in the spirit of Open Science, to advance knowledge, ensure integrity, maximise the value of research output and sustain long-term impact.

The RDM Principles affirm our shared commitment to responsible research data practices and set out the values guiding the creation, stewardship, sharing, and preservation of research data across the institution and in collaborations. Through coordinated support and guidance, we help every researcher contribute to a strong, ethical, and future‑ready data ecosystem.

UniLu staff can access research data management internal guidance on the Intranet.

Guiding principles

• Early planning

  A data management plan (DMP) is expected to be created at the outset of a project. Plans should evolve with the project, addressing data collection, documentation, storage, access, sharing and preservation.

• Protecting data

  Personal and sensitive data should be managed in compliance with ethical approvals, GDPR, and institutional policies. Safeguards should be proportionate to the sensitivity and risk level.

• Respecting ownership

  Intellectual property, contractual obligations, and licensing requirements must be observed, including those of collaborative, funded, or externally partnered projects.

• Ensuring quality

  Data should be documented with rich metadata and contextual information to ensure datasets remain understandable and reproducible, supporting verification, reuse, and future research impact.

• Storing securely

  Responsible data handling through the lifecycle, and institutional storage solutions should be used to safeguard against data loss, corruption, or unauthorised access.

• Sharing responsibly

  Data should be made openly available in trusted repositories whenever possible, without conflict with intellectual property requirements. Sharing must follow the FAIR principles (Findable, Accessible, Interoperable, Reusable), while respecting legal, ethical, and commercial constraints.

• Preserving for the future

  Datasets of long-term value should be archived for at least 10 years after the end of the project, as required by the UNI Records Retention schedule, in line with disciplinary standards and funder requirements. Preservation ensures accessibility, authenticity, continuity, compliance, transparency, and future reuse.

• Collaborating with support services

  Researchers are encouraged to engage with institutional RDM resources, including the library, research facilitators, data stewards, and other support services, etc. These services provide expertise to ensure compliance, efficiency, and best practices.

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  RDM guiding principles