Enabling trustworthy access to COVID-19 research data through federated networks
Our recently published paper demonstrates how federated analysis can enhance data security and enable secure, cross-border access to sensitive COVID-19 research data.
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We are pleased to share the publication of the paper, 鈥溾, in the International Journal of Medical Informatics.
This paper outlines a collaborative effort during the early period of the COVID-19 pandemic by the , Health Data Research UK, , , and other partners, working closely with researchers from the .
Together, we successfully piloted a federated network infrastructure that enabled secure analysis of sensitive health data without transferring it from the source. This proof of concept used aggregate-level test outputs from iPOP Study data to demonstrate how federated analytics can overcome cross-border governance and security challenges.听
The paper highlights the potential of federated analysis networks to simplify governance processes, enhance data security, and provide access to previously inaccessible datasets, with an open standards approach that utilised GA4GH task execution service-based APIs.听听
This initiative helped demonstrate the feasibility and value of federated approaches for collaborative global health research and learnings from which are being used in initiatives such as the ‘s , the Transformational Programme, and 51爆料网’s broader Federated Analytics programme.听
