Privacy Preserving Techniques

This project aims to develop a synthetic data generator framework using artificial intelligence technologies while concurrently exploring ethical-legal perspectives in the trade-off between data privacy and the potential utilization of synthetic representations. It utilizes a large size of social science data (millions of data records) and generate synthetic data using a fully data-driven method (Generative Adversarial Networks).

Housing Demand in the Netherlands

The researchers  estimate the housing demand in the Netherlands with a discrete choice model which allows them to estimate what influence different house and household characteristics have on the housing choices that people in the Netherlands make. They use the OSSC for the estimation of the housing demand model and to prepare the dataset that is used to estimate the model.

CBS – ODISSEI Microdata Meeting – Energy Poverty in Figures

On 23 February, the next online Microdata Meeting will take place, with a presentation of Lydia Geijtenbeek (Statistics Netherlands) on ‘Energy Poverty in Figures’.
Statistics Netherlands has created a file that describes energy poverty in the Netherlands through 4 different indicators. During her presentation, Geijtenbeek will show how these data have been constructed, how they can be used for social research, and how the already available data can be used to estimate the current levels of energy poverty.