350k€ TDCC-SSH challenge grant to make sensitive data more accessible through synthetic data

Erik-Jan van Kesteren (Assistant Professor, department Methodology & Statistics) has obtained a grant as PI of a small consortium of SURF, DANS, and Maastricht University to work on synthetic data solutions for existing sensitive SSH-domain datasets. Synthetic data is a dataset with (more or less) the same properties as an original dataset but without privacy-sensitive information. By making synthetic data available instead of (or prior to) the actual dataset, scientists gain faster and easier access to confidential data. The project will last for 2 years.