Trusted Research Environments: Analysis of Characteristics and Data Availability

Martin Weise ¹ Andreas Rauber¹

¹ TU Wien

Evidence-based research relies on high-quality data from trusted sources. These Trusted Research Environments (TREs) enable analysis of sensitive data under strict security assertions who protect the data with technical, organizational and legal measures from (accidentally) being leaked outside the facility. Our literature study shows that 47 TREs worldwide provide access to sensitive data of which two-thirds provide data themselves (n=32, 68%), predominantly via secure remote access (n=46, 98%). Statistical offices (n=13, 28%) make available a majority (n=1.3 M, 92%) of available sensitive data records included in this study.

Run

We used Python 3.10 and DBRepo 1.4.0 during our analysis. First create and load the virtual Python environment:

python3 -m venv venv
source ./venv/bin/activate

Install the Python dependencies from the Pipfile for the Jupyter Notebook:

pipenv install

Start the Jupyter server:

jupyter notebook

The supplementary material is located at https://gitlab.tuwien.ac.at/martin.weise/tres and is also deposited at DOI: 10.48436/cv20m-sg117.