Open Research data

According to Open Definition Open Data is:

“Open data is data that can be freely used, re-used and redistributed by anyone – subject only, at most, to the requirement to attribute and sharealike.”

The Open Data Handbook provides a guide to legal, social and technical aspects of open data.

Because the organisation and use of data via data centres and data sharing is becoming more and more important for research, it is essential that not only publications but also research data be openly accessible. Because of the added value it brings, Open Data is especially worthwhile and gives research completely new opportunities. Research data can be integrated in publications, documented indirectly, for example via links in publications, or made available in the form of independent data sets.

How to make research data open?

There are three steps you can take to make data available:

Step 1:

Choose your dataset(s).  There might be legitimate reasons not to share data e.g. for intellectual property rights (IPR) concerns, privacy/data protection concerns, national security concern. Carefully considerate the dataset(s) you plan to make open. Keep in mind that you can (and may need to) return to this step if you encounter problems at a later stage. Choose a well managed dataset. A data management plan might help you organize and prepare your data for consultation and re-use.

Step 2:

Find a research data repository. Find a data repository that matches your data needs and discipline. An overview of repositories can be found at Re3data. If there is no subject-specific data repository available, catch-all repositories such as Zenodo, provide a good alternative. If you have trouble locating a suitable data repository, contact your institution. Publishing in a data journal is also an option. 

Step 3:

Deposit your data. Deposit the data and the information necessary to access and use it, i.e. metadata and tools/instruments, in the data repository. Attach an open licence, such as a creative commons license, to the datasets that can be made openly available.The idea is that whoever comes across your dataset is able to understand and use it without having to contact the original owner. 

More about

Data Management Plans

A Data Management Plan (DMP) is a formal document that specifies how research data will be handled both during and after a research project. It identifies key actions to ensure that research data are safe, sustainable and – where possible – accessible and reusable. A DMP should be considered a ‘living’ document – it is ideally created before or at the start of a research project, but updated when necessary as the project progresses. You can find different templates of DMPs in the online tool: or


It is important to consider the costs (both in time and money) of Research Data Management. Some funders might reimburse costs for research data management. Keep in mind that proper data management involves far more than just storage for your research data. To estimate the costs of RDM and resources needed for your research project, you also need to take into account all other relevant activities throughout the whole data life cycle.

Some tools and checklists are available to help you work out the costs of RDM:

Schematic overview of steps to take towards opening up research data

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