Consulting: Privacy in open data
The past six months we consulted for the Meta-Research Center on their NWO Open Science Fund project, aimed at detecting privacy violations in datasets.
The past six months we consulted for the Meta-Research Center on their NWO Open Science Fund project, aimed at detecting privacy violations in datasets. You can now use the web app we built and the R package we developed to scan your datasets and prevent sharing privacy violations.
Together with prof. dr. Jelte Wicherts and dr. Rick Klein, we wrote the original grant proposal to improve scanning for potential privacy violations in datasets. After we observed in a previous study that 1 in 20 datasets contain identifying information, we determined more work was necessary to improve the situation. The NWO Open Science Fund made this possible.
In the project, we conducted a controlled study to investigate how well our algorithm worked to identify potential privacy violations. All in all, we were able to retrieve technical identifiers (e.g., email, IP addresses) with high sensitivity and precision, and high risk direct identifiers as well (e.g., gender, bank information). Find the detailed results in the precision report on ResearchEquals.
We documented all the steps for this project on ResearchEquals and shared the source code openly on GitHub. The following diagram showcases the development of the project, from before the grant proposal was written to the current state:
Practical next steps include the screening of datasets by using the
datacheck R package or the
datacheck web app, so that you can prevent sharing privacy violations yourself. This algorithm can also be applied in editing processes for journals more widely. Are you interested in a walkthrough? Check out our project report on YouTube.
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