Data sovereignty

Data sovereignty is the principle that data is subject to the laws of the jurisdiction where it is stored or processed. It shapes how governments and organizations choose data locations and manage cross-border access.

Data localization: Data localization requires certain data to be stored or processed within a specified jurisdiction. It turns jurisdictional control into a concrete requirement about where data must reside.
General Data Protection Regulation: The General Data Protection Regulation is the European Union's comprehensive law governing personal-data processing and protection. Its rules constrain transfers of personal data beyond the European Economic Area.
Data privacy: Data privacy concerns the appropriate collection, use, sharing, and protection of information about people. Privacy focuses on permissible handling; sovereignty focuses on jurisdictional authority.
Schrems II: Schrems II is a 2020 Court of Justice of the European Union judgment invalidating the EU–US Privacy Shield. The judgment made transfers depend on whether foreign surveillance laws undermine EU protections.
Data colonialism: Data colonialism describes the extraction and appropriation of data through relationships of economic and political power. It questions whether sovereignty protects communities or mainly strengthens state and corporate control.
Conflict of laws: Conflict of laws determines which jurisdiction's rules apply when a matter connects to multiple legal systems. Cloud data can connect to the laws of its storage location, provider, and users.
Cross-border data flow: A cross-border data flow is the transfer or access of data across national borders. Sovereignty concerns arise when data moves between jurisdictions with different laws.
Data security: Data security comprises measures that protect data from unauthorized access, alteration, loss, or disclosure. Security protects data against threats but does not determine which laws govern it.
EU–US Data Privacy Framework: The EU–US Data Privacy Framework is an arrangement governing certain personal-data transfers from the European Union to the United States. It is a policy response to legal challenges over transatlantic data transfers.
Federated learning: Federated learning trains machine-learning models across distributed devices or institutions without centralizing their raw data. It may reduce data movement while leaving questions about model access and legal jurisdiction.

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