Some tips on sharing data

There are many shades of data sharing: on the one end of the spectrum there are data which are only available to one researcher, on the other end there are data which are available to anyone ('open data'). In between both ends is a whole world of possibilities:

  • In order to share data it helps if you store your data where other researchers can access it, e.g. in a public repository. If you take care that your dataset is assigned a persistent identifier, others can simply and correctly refer to the (correct version of) your data.
  • Since it is not allowed to publish personal data, datasets with personal data must be anonymised (for tips on this: Also, respect the rights stated in the informed consent.
  • In order to keep your research data usable to yourself and others, it is recommended to document your data: record all the information necessary to understand the content and context of the data. In your documentation you need to include information on the collection of the data, the data input, the data storage and the data processing. Lab journal or codebook also count as documentation of a dataset and, if possible, are stored with the data.
  • In order to make sure that your dataset will appear as a search result, you must assign information to the dataset which can be read by search engines: metadata.
  • When sharing data, it is important to document any conditions for reuse. Documentation should include a description of any standard licenses applied to the data, as well as any additional terms of use. By providing your dataset with a End User license, it is made clear to others what they are or are not allowed to do with your dataset. An existing dataset may be combined with another existing dataset, or supplemented by data collected by yourself. If you wish to make the resulting dataset available for reuse, you must take the license(s) of the original dataset(s) into account.

Intellectual property issues related to research data are complex. Ownership of data may rest with the researcher, the institution, or the funder, depending on the nature of the researcher's appointment, grant contract conditions, and whether there are patent implications.

Researchers may have ethical or legal obligations to maintain confidentiality and to protect the privacy of research subjects, or may have other circumstances requiring secure data storage or restricted access to data, such as licensing restrictions that prohibit data sharing. Data may also be part of a research project with commercialisation potential. Funders and publishers recognize that there are legitimate circumstances under which an investigator cannot share their data, and a data management plan should explain those circumstances.