This investigation explores federated computing to enhance data integration while preserving autonomy and compliance in multiple jurisdictions.
Modern research and business organizations often require information integration from multiple sources, creating a fundamental tension between the need for collaboration and the obligation to maintain autonomy, data security and regulatory compliance. Building on prior work that introduced federated computing (FC) as a data-driven approach to business infrastructure, this article investigates its theoretical foundations. We formalize four foundational principles that align the architecture with policy requirements: distributed data assets, federated services, standardized application programming interfaces (APIs) and decentralized governance. Although necessary, these principles cannot guarantee system-wide coherence without a federated orchestration layer to ensure that distributed components remain aligned as policy, context and computation evolve independently across jurisdictions. Central to our analysis is a novel value–identity model that reconciles collaborative data use with the preservation of sovereignty. Our investigation provides theoretical insights into the requirements for distributed coordination, privacy-preserving data transformations and the integration of governance architecture. A pharmaceutical research case study illustrates how FC enables multi-jurisdictional analytics without centralized control. FC establishes the conceptual foundations for integrating sovereignty-aware data and services in large-scale, multi-stakeholder environments at the intersection of information systems, governance and architectural design.
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Fenoglio et al. (2026) studied this question.
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