Although big data (including personal data) has become widespread and minable, datasets available to researchers for scientific enquiry are not so easily available, only under restricted regimes, or they vary in quality. Another important limitation to using these datasets is the respect of data protection regulations put in place by the European Union legislation (for instance GDPR). Proposals are expected to propose new strategies and approaches on how to deal with data, and the lack thereof, in a way that fully complies with the EU’s notion of privacy and personal data.

A promising avenue in this respect is the creation and use for research of synthetic data sets, including full-scale synthetic reference populations. Those can link, while not interfering with personal data use restrictions, highly granular data set. As a result, empirical analysis can much better cater for distributional impacts across a wide range of types of households, and individual socio-economic backgrounds, and the impact of socio-economic policies in different geographical settings can be studied at the same level of detail as currently the case in environmental studies.

Thematically, proposals may choose whichever research focus, in the area of democracy, deemed relevant to exploit the potential of CCS. They may concentrate on testing age-old questions of political economy and political sociology and see how they change or survive when tested in a highly granular simulation environment, as synthetic population data allows to do, or they may identify more recent topics such as political communication, political participation, or resilience of democracies, in relation to structural socio-economic patterns.

Proposals should leverage the data and services available through European Research Infrastructures federated under the European Open Science Cloud, as well as data from relevant Data Spaces in the data-driven analyses.