ArticleInternational journal of population data science2026
E-Research Institutional Cloud Architecture (ERICA): An Orchestration Meta-Framework for Establishing Trusted Research Environments Using Public Cloud Computing.
Article in International journal of population data science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors.
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Abstract
Introduction: The E-Research Institutional Cloud Architecture (ERICA) is a code-driven orchestration framework that automates the configuration and management of Amazon Web Services (AWS) resources to provide trusted research environments (TREs) for sensitive data. Independent ERICA TREs are now operational in universities and government agencies. The framework was developed by the University of New South Wales, Australia, with support from the Australian Research Data Commons. Objectives: ERICA was designed to overcome the limitations of traditional on-premise TREs by providing secure, scalable, and flexible cloud environments that protect privacy while enabling advanced, data-intensive research. Approach: Using an infrastructure-as-code model, ERICA delivers consistent, reliable, and error-free setup of Project Spaces. It integrates robust security features, including encryption-at-rest and in transit, and multi-factor authentication. Hosted in AWS onshore data centres, ERICA ensures data sovereignty while supporting diverse operating systems and high-performance computing configurations. The architecture also allows rapid deployment of new AWS services, including generative AI tools, within research workspaces. Discussion: ERICA implements the Five Safes framework-covering safe projects, people, data, settings, and outputs-to ensure compliance and secure research. Its modular architecture enables multiple independent TREs, each governed by host-institution policies and capable of supporting hundreds of Project Spaces. This flexibility allows replication across any jurisdiction with AWS public cloud infrastructure. However, reliance on AWS introduces challenges, including charges in US dollars and delayed rollout of new services in smaller regions. Conclusions: ERICA represents a step change in providing privacy-by-design cloud infrastructure for sensitive, data-intensive research. By combining strong governance with the scalability of AWS, it enables researchers to work securely with large, complex datasets while rapidly adopting cutting-edge analytical tools. ERICA TREs offer a replicable, future-proof model for supporting secure research at scale.
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