A long-standing problem among researchers is the possibility of performing analyses on integrated granular data from different sources and to collaborate using them.This limitation comes from the implementation of GDPR-compliant procedures and the necessity of combining data based on the principles of transparency, fairness, and limited purpose set by GDPR.

This report presents results of pilot studies that rely on recently developed privacy-preserving technology (synthetic data) that can potentially overcome some of these limitations.

We discuss applications in education economics, comparing results of the same analysis across different case studies that can be scaled up.

We then performed a meta-analysis and illustrated how much the general public could learn from gaining access to such data in a common format.

We show that this technology can offer interesting opportunities but, at the same time, some challenges remain to be solved.