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Research Data Management (RDM) at ET

Good scientific practice is one of the main reasons to manage research data during and archive the data after the project. It is important to keep available the raw, processed and/or analyzed data, as well as the documentation necessary for understanding the data and the way it was collected, processed and analyzed. This plays an important role in accountability issues, and allows the researcher to reuse his/her own data or to return to earlier stages of the research process when needed. As a result, research will be reproducible and verifiable. Proper research data management (RDM) makes science more transparent, and improves scientific integrity and societal trust.

Data Management Plan (DMP)
Each individual researcher or research leader is responsible to write a research data management plan. The researcher should do this at the start of the research project. The UT has developed a tool for writing your data management plan (DMP) and the notification of processing of personal data in research in compliance with the General Data Protection Regulation (GDPR registration). 
NWOZonMw and EU approved the UT DMP template. This means that you can complete the UT DMP template and upload this template in finalizing your grant procedures. Please check the general UT website on Data Management (and the RDM courses), the UT and ET data policies and Guidelines on personal information. The Canvas course is available to everyone. The Bootcamp course is mandatory for PhD's (including Canvas courses, interactive session and DMP review). All practical and general information about RDM, can be found at

If you have any questions regarding Research Data Management or specifically about the tool, please contact:

RDM Policy

How to store/share/transfer data

Find the best way to store, share or transfer your research data by using this decision tree