TDCC-SSH synthetic data project

Synthetic data is data with (more or less) the same properties as an original dataset but without its 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. In this project, two tools for creating synthetic data are used to unlock existing datasets, including datasets archived at DANS.

Work packages

Package	Title	Description
WP1	Synthetic data generation tools	Creating open source software (metasyn and DP-CGANS) to produce privacy-friendly and realistic synthetic data.
WP2	Integrating tools in data repositories	Creating a plug-in to allow synthetic data generation in DANS Data Station SSH in the ingest pipeline and/or the user interface.
WP3	Synthetic data use-cases in SSH	Creating pilot implementations of synthetic data at various partner institutions.
WP4	Legal and privacy constraints	Creating a whitepaper or publication on how to overcome implementation issues with synthetic versions of sensitive data.
WP5	Outreach and project management	Organising events, creating teaching materials, and ensuring our project runs smoothly.

Package

Title

Description

WP1

Synthetic data generation tools

Creating open source software (metasyn and DP-CGANS) to produce privacy-friendly and realistic synthetic data.

WP2

Integrating tools in data repositories

Creating a plug-in to allow synthetic data generation in DANS Data Station SSH in the ingest pipeline and/or the user interface.

WP3

Synthetic data use-cases in SSH

Creating pilot implementations of synthetic data at various partner institutions.