This project uses nationwide individual-level register data from the Netherlands to study the relationship between problematic debts and mental health. The researchers use the OSSC to run the algorithm on millions of observations.

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. The project uses a fully data-driven method and the ODISSEI Secure Supercomputer to conduct computationally expensive experiments.

How has car ownership in Amsterdam changed since the opening of the North-South metro line? This research project utilizes CBS microdata of residents of Amsterdam of the past 10 years to disentangle that complex question.

What are the effects of factors such as air pollution, noise and greenery on the health of adults based on country-wide questionnaires and registrations? This project by researchers at RIVM is highly complex and requires a great deal of computing power.

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.

What can we learn about Dutch residential planning policy from past experience? In cooperation with Utrecht University, the Netherlands Environmental Assessment Agency (PBL) is researching the long-term effects of the VINEX policy.

Who uses the healthcare system and when? Obviously people use it when they get ill, but is everyone as likely to use it for the same conditions in the same way? In this study, researchers from VU Amsterdam examine whether there are specific characteristics which are associated with health care usage and that might explain differences in health outcomes in the population.

In this groundbreaking study, Statistics Netherlands linked the records of 16.9 million people, identifying their family, their neighbours, their schoolmates, and their colleagues. The resulting network allows researchers to understand how behaviour and inequalities spread across the population and where strong and weak ties exist between various groups in the population.

In this remarkable study by researchers at TU Delft, high resolution geo-spatial data are rendered for the whole of the Netherlands and identify the distribution of populations, poverty and deprivation at an unprecedented scale in order to better understand how our local neighbourhood shapes our own lives.