Training & seminars

Training ‘Writing a Data Management Plan’ voor PhD students

Practical organisational issues
The University Library is organising a training called ‘Writing a Data Management Plan’ aimed at PhD students. You learn how you write a good Data Management Plan (DMP), in which you discuss:

•    which laws and codes of conduct your research should comply with,
•    where you are going to store your data,
•    where you are going to archive them for the long term,
•    how you can make them FAIR (Findable, Accessible, Interoperable, Reusable).

The training is tailored to the faculties of VU Amsterdam and we organise it in collaboration with the university graduate schools and PhD coordinators. Below you can find how the training is being organised in your faculty. If the training is embedded in another course taught in your faculty, we recommend getting in touch with your graduate school for the planning (see below). Registration forms for the independent training sessions can be found in the Library Event Calendar.

The training is also embedded in the course about High Performance Computing (HPC) taught at VU Amsterdam. In case you are interested in HPC, you also have the opportunity to take the session about writing a DMP there. 

From 2020 onwards, the course will no longer be organised for VUmc. If you are interested in a course about Research Data Management at VUmc, please get in touch with

Do you have questions about the content of the training or practical issues? Please contact

Embedding in curriculum
More information
Next training session (status 6-1-2020)
Independent training
To be scheduled, contact
Independent training
(together with FGB)
29-1-2020 (GDPR),
31-3-2020 (GDPR)
7-5-2020 (without GDPR)
Independent training
(together with Bèta)
29-1-2020 (GDPR),
31-3-2020 (GDPR)
7-5-2020 (without GDPR)
Embedded in the course
'Research Integrity'
November 2020
Embedded in the online
course 'Research Design'
See the FRT graduate school's website
or contact
February-March 2020
Independent training
See the FSW graduate school's website
or contact
Independent trainingContact
Independent trainingContact
Part of HPC course
See the HPC-website
In the fall of 2020

Description of the content of the training
Good RDM (e.g. storing, sharing, archiving, describing your research data) contributes to research transparency and integrity. Due to the advance of new technologies for data collection, numbers of files  and data volumes and are constantly increasing. For that reason, good data management is an essential part of data-driven research as well. In this workshop, we will introduce and discuss the different aspects of RDM which typically need to be covered in a DMP, such as data description, data storage during research, sharing data with colleagues, data archiving after research and data citation. The various components of research data management will be related to the FAIR principles (that is, principles to make data Findable, Accessible, Interoperable and Reusable). We will also address the ethical and legal framework, including the General Data Protection Regulation (GDPR) for groups for which this privacy legislation is applicable.

In this training, you’ll learn why good RDM is necessary and how it can be beneficial to your research. In an interactive workshop, we will provide you with practical guidelines and instruments to manage your data properly.  You will be working on a DMP for your own research, so that you can apply the things you learn to your own project.

Details for FGB and Bèta
The combined course for FGB and Bèta will be taught in two different versions: one for research with personal data (in the sense of the GDPR) and one for research without personal data. When registering for the course, please make sure that you sign up for the right version.

If you sign up for this training, we expect that you do the requested preparation before the workshop. You will be asked to study some materials about RDM (two short articles and a website) and to write a first draft of your DMP.

•    Estimated time investment for the preparation: 20 hours
•    Credits for this course: 1 EC

Detailed overview of time investment:
Preparation (reading materials)
10 hours
Study DMP templates and choose one for the assignment
2 hours
Write first draft of DMP
8 hours
Discuss DMP with your supervisor(s)
1 hour
3 hours
Finalise your DMP
4 hours
28 hours (= 1 EC)