Alternatives to sharing personal data

On this page: metadata, documentation, information, publication, share, transfer, open science, FAIR data, reproducibility
Date of last review: 2023-03-09

Publish metadata and documentation

Even if you cannot share/publish the data, you can still publish non-sensitive metadata and documentation surrounding your research project. This allows your dataset and documentation to be findable, citable, and in some cases even reusable (one person’s metadata is another person’s data!). In order to make the dataset FAIR, you should include a note on the access restrictions of the dataset and choose a good data repository. Knowing that your dataset exists can sometimes already be useful information, even when the data are not accessible for others. For an example, please refer to the use case about the Open Science Monitor.

Use other techniques and strategies to enable reuse

There are also more technical alternatives to transferring personal data to others:

  • Use solutions that allow others to run analyses on your data, without ever needing access to those data (remote data science, see the Secure computing chapter).
  • Create a synthetic dataset that others can use to reproduce trends or explore the data.
  • Only allow differentially private algorithms to query your dataset.
  • Publish aggregated (anonymous) data which may still be useful for others (e.g., group-level statistics).