The primary goal of research data management is to ensure that research data is of high quality, securely stored, and easily accessible for future reference, verification, and reuse. Effective research data management practices save time by conducting your research in an efficient way and reduce risk of data loss, enhance the reproducibility of research findings, promote collaboration, and contribute to the overall integrity and credibility of scientific research. Such practices also help you get recognized for your work.
RDM helps you comply with internal and external requirements (TU/e Code of Scientific Conduct, VSNU Code of Conduct for Research Integrity, GDPR, Funder requirements ). Many institutions and funding agencies now require researchers to have clear data management plans in place as part of their research projects.
For a quick start, check our general RDM guidelines and FAQ.
RDM – related topics
Information about funder requirements, data management plan, RDM costs, and ethical approval.
Information about using existing data, FAIR, organization and documentation of your data, storing and sharing data.
Information about long-term storage, archiving, and data repositories.