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.

LISS Grant awarded to nine researchers

The results of the LISS-call 2020 are in. Proposals from nine researchers at ODISSEI member organisations were awarded the grant. Via the grant, the researchers will get access to free panel time. The LISS panel, managed by CentERdata, gives researchers access to survey data from about 7,000 respondents from approximately 4,500 households.