a. Basic documentation

Some basic documentation steps include registering your research project at your UMC, organising your files in a clever way and keeping your data management plan up-to-date.

Register your study

The GDPR demands registration for any study that involves personal data.

In the Netherlands, all medical research with human subjects is also registered at the CCMO register, before they start.

Organise your files

Once you start creating and processing data, the files can easily become disorganised. Naming and organising your files in a clever way (i.e., a naming convention) saves time and prevents errors. The best time to think about this is at the start of your project. Your UMC may offer a general structure for naming and organising files. Decisions about naming files should be shared with all people involved in the project.

If you have a large number of data files or very large files, you should keep a master list with critical information about your files and their purpose (including links to the files).  Your master list should be properly versioned, so that all changes are registered over time along with their reason. The list should ensure that everyone involved in the project agrees what is the latest version.

Keep your data management plan up-to-date

Remember that data interpretation crucially depends on knowledge of the data collection process as well as methodological knowledge. Of course, the amount of documentation required varies between studies.

You need to properly document all steps of your research in your data management plan:

  • documentation of informed consent, broad consent or no objection per study participant;
  • documentation of agreements and decisions;
  • experimental notes (e.g., in lab notebooks, lab journals, etc.);
  • document the origin of all stored data and make this verifiable. In addition, make sure that the selection processes that have led to the actual storage are verifiable;
  • possible changes in the operational workflow;
  • changes to the research data;
  • metadata;
  • reference of the data collection in a metadata catalogue;
  • used IT standards and code book.

Frequently Asked Questions

We recommended storing your raw data and all versions after meaningful processing steps that you cannot easily repeat. At least store the raw data that you use as the basis for your publications, including the descriptions of how you obtained these data and how you processed them (metadata). Ensure that it is clear which metadata describe which data. Also store the various scripts that you use in combination with the datasets.

It may be necessary to keep intermediate data for the sake of reproducibility. If this is not the case, you can consider deleting intermediate files produced during data processing to save storage space and to reduce the risk of inadvertent privacy violations. You can also exclude them from a backup scheme to save time on a possible restore after hardware failure.