Research data are valuable research outputs and should be managed throughout their entire lifecycle to ensure they remain findable, accessible, interoperable and reusable. Today, good Research Data Management is an integral part of high-quality research and is increasingly expected by universities, research funders, publishers and the wider scientific community. The FAIR principles provide the foundation for effective research data management, while Open Science practices promote transparency, reproducibility and the responsible sharing of research outputs. Beyond meeting institutional or funder requirements, adopting good RDM practices helps researchers organise their work more efficiently, reduce the risk of data loss, protect sensitive information, facilitate collaboration and maximise the visibility and impact of their research.
Effective Research Data Management is what makes research outputs verifiable, citable and reusable. It is a continuous process that begins at the very start of a research project and continues beyond its completion. Our training programme follows the entire research data lifecycle, providing practical skills that can be immediately applied to your research. The five courses cover the key stages of Research Data Management, including Open Science requirements in European and National funding programmes, Data Management Plans, the responsible management of sensitive data, research software management and the publication of datasets in trusted digital repositories (such as Dataverse UNIMI). A DMP is not simply an administrative requirement: when prepared at the beginning of a project, it helps organise research activities, clarify responsibilities and plan for the preservation and sharing of research outputs. Likewise, publishing data and, where appropriate, research software in trustworthy repositories increases their visibility, transparency, interoperability and reuse.
You may find these courses particularly useful if you are asking yourself questions such as:
- How open should my research data be?
- What are the Open Science requirements in Horizon Europe and other EU funding programmes?
- How can I manage sensitive or personal data responsibly?
- How should I organise and document research software?
- Where can I publish my datasets to obtain a DOI and comply with journal or funder requirements?
- Can a Data Management Plan be useful for my project?
Ready to strengthen your Research Data Management skills? We recommend starting with our 5-minute introductory module on the FAIR Principles, which provides the essential background for the rest of the training pathway. You can then enrol in one or more of our online courses covering the main topics of Research Data Management and Open Science: click on the course title below to open the registration form and choose the training most relevant to your research.
These courses are part of the Research Data Management and Publishing training pathway. Each course can be attended independently, and a certificate of attendance is issued upon completion of every course, but we encourage participants to explore the other courses in the programme and complete the full pathway. We are currently exploring ways to formally recognise the completion of the full training pathway.
More information about all Open Science available courses is available here. For any doubts or queries on the trainings, you can contact us at rdm@unimi.it