Research Data Life Cycle

Before research

  • In many cases, writing a data management plan (DMP) can help you to organize and plan your research data management. Most research funders require you to write a DMP before you can start your research project. This also includes budgeting the costs for research data management.
  • Consider whether you need to create new data (and in which format) or can reuse existing data that you or others have created before.
  • Think about what data you want to collect. Are there ethical concerns, for example because you will be dealing with personal and/or sensitive data? If so, you need to register your research project for ethical review. Moreover, contact the data stewards of the RDM support team ( in order to perform an assessment of the privacy risks of your project.
  • If you are writing your own software, consider if you want to make that available for reuse.
  • Are you collaborating with (external) partners? You might need to draw up agreements, for instance about data transfer or data processing.
  • Make sure you are aware of the FAIR principles.


Preregistration is the practice of depositing your research question and research plan before conducting a study. Although preregistration is more common in gamma and medical sciences, it is spreading into other fields. Preregistration increases the credibility of your results and allows you to stake your claim to your ideas earlier. Preregistration is a way to plan for better research and increases transparency. It avoids unnecessary duplication of studies, reduces reporting bias and creates opportunities for collaborative research.

Preregistration tools often used in the field of psychology and medical research:

During research

  • Stick to your DMP but adapt it if necessary. A DMP is a living document and it should be reviewed and updated as your research project progresses.
  • During your research, you must make sure the data you collect or reuse is stored and potentially shared safely and securely. Storage on TU/e-approved facilities (e.g., secured networked drives or cloud storage in SURFdrive or Research Drive) is preferred over local storage on your own private hard drive or laptop.
  • In case you are processing personal, sensitive, or special categories of data, additional safeguards may apply. You may need to anonymize, pseudonymize, or encrypt the data.
  • Make sure that you organize your data and provide your data with appropriate documentation and metadata. This will help you to understand your data and facilitates sharing later. It is easier to provide (detailed) metadata at this stage than after the project has finished.

After research

  • Consider what data should be stored for the long term and what data should be deleted for safety reasons (e.g., sensitive data).
  • Add metadata to your data.
  • Carefully consider what part of your data you want to make (publicly) available. You may already have outlined these decisions in your DMP. What data do you want to retain and what data can be removed (e.g., raw vs. processed data)?
  • Deposit the data and software you want to share in a searchable repository so that a persistent identifier is added to the data. Add metadata and appropriate documentation, and choose a license.
  • Link your data to your publication. Refer to your data-DOI in your publication and to your publication -DOI in the metadata of your deposited dataset.
  • Register your dataset in Pure and link it to your publication. Note that research data is also research output.