a. General considerations

A data management plan (DMP) shows that you have thought about how to create, store, archive, and give access to your data during and after your research project.

Taking the role of a data steward, you should always be able to describe the complete operational workflow for your research data, from data capture, to data analysis, archiving, and sharing. A DMP helps you to think this through. You are responsible for answering questions about the origin of your data, data manipulations, the location where the data are analysed and archived, and with whom they are shared under what conditions.

Your UMC should provide a standard workflow description for researchers, a general data management infrastructure that is compliant with current regulations and guidelines, and DMP templates. We therefore advise you to contact experts at your UMC to help you with these issues; you can use the toolbox to locate experts and find resources.

Figure: Example of an ‘operational workflow chart’.

In your data management plan, you describe all the relevant steps and functionalities that are shown in the chart. This may help to create an overview. This example shows the typical activities around clinical data, including repositories.

Frequently Asked Questions

Funding bodies require varying degrees of data management planning at the grant proposal stage and after grant awarding. Many research funders request that you:

  • create and follow a data management plan;
  • create FAIR data;
  • share some or all of your data with the public;
  • share some or all of your data for further research or verification of your research results.

Recently, ZonMW announced (and others may follow) that it will accept data management plans based on UMC DMP templates, on the condition that these contain (at least) these 5 features:

  1. a link to the repository, online catalogue or web portal on which the data or the associated metadata will be listed mentioned;
  2. the DOI code (persistent identifier), ensuring that the data collection can be found in the long term;
  3. the link (or persistent identifier) to the terms of use of the data (this is not required if the data collection is open access);
  4. the metadata standard that you intend to use, which facilitates data linking;
  5. the link to the archive or repository for long-term archiving.

You can use a variety of techniques to generate data. Familiarity with one technique does not necessarily make that technique the best for your particular study. You should consult experts to make sure you make a good choice.

Careful study design is required to ensure that your research question can be answered in the end. For instance, you should select the most appropriate technique and determine the sample size required to get statistically meaningful results. Scientific reviewers and ethical committees tend to carefully look at this aspect, especially when patients or animals are involved. Study design is the domain of specialists, who can be consulted in the design phase of the study. In addition, you can follow basic courses on study design, good clinical practice, and research data management.

A statistical analysis plan is mandatory for randomised controlled trials and it is advisable in the majority of other studies. You should create the statistical analysis plan prior to analysing your data, but it is preferable to create it even before you start collecting data. This is because it facilitates proper study design (e.g., inclusion and exclusion criteria, number of study subjects needed, decisions with regard to statistical power, choice of data items to be collected) We recommend having the plan validated by a statistician.