Containers as Secure Processing Environments (SPE) to deploy federated research architectures reusing health data

27 February 2024

Webinar online 27 February 2024, 15:00-16:45 CET

Containers, constructed using software like Docker, can be used to package code executing statistical analyses together with the required dependencies and can provide a fixed Secured Processing Environment (SPE). Distributing code to execute statistical analyses reusing sensitive health data in a federated research network can benefit from using containers, ensuring the reproducibility of analyses in federated analysis architectures.

Audience:

This initiative targets researchers producing and/or working with sensitive data and individuals with a more technical background who actively support these researchers. This can include participants from the BY-COVID WP5 baseline use case, any BY-COVID partner or anyone interested in the topic.

Prerequisites:

Participants should have basic knowledge about containers or have someone in their institution who knows how to create containers but needs to gain experience in deploying them in the context of sensitive data analyses.

Teaching objectives:

• Raise awareness of the significance of employing containers for disseminating and deploying statistical analyses, focusing on responsibly reusing sensitive health data within a federated research network.

• Cultivate a sense of trust and confidence in using containers for the distribution and deployment of statistical analyses, particularly in handling sensitive health data within a federated research network.

• Explore and identify the organisational requirements and potential barriers to implementing containers for this specific purpose within their respective institutions.

• Guide participants in troubleshooting the challenges they encounter, providing practical solutions to address issues related to the deployment of containers for statistical analysis in a federated research network.

Preparatory reading:

Meurisse M, Estupiñán-Romero F, González-Galindo J, Martínez-Lizaga N, Royo-Sierra S, Saldner S, et al. Federated causal inference based on real-world observational data sources: application to a SARS-CoV-2 vaccine effectiveness assessment. BMC Medical Research Methodology. 2023 Oct 23;23(1):248.

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