2025: A Data Space Odyssey

In this piece, author Nik Roeingh (European Law Blog) examines the European Union’s strategy for achieving digital sovereignty through Common European Data Spaces (CEDS), arguing that data sharing is essential for Europe to compete with the United States and China in artificial intelligence and digital innovation. Roeingh explains that while the US is dominated by data monopolists and China maintains state control over citizen data, Europe must develop a framework that enables data accessibility while protecting core values like privacy, self-determination, and fair competition. The author emphasizes that without access to large-scale, high-quality datasets through coordinated sharing among multiple companies and sectors, Europe will continue to lag behind in AI development and productivity.

The article describes CEDS as purpose- or sector-specific frameworks based on distributed data architectures and semantic integration that enable trustworthy data exchange through commonly agreed rules and standards. These data spaces are designed to reduce information asymmetries and unlock the potential of data currently distributed across numerous European actors, particularly small and medium-sized enterprises. The European Commission has established a regulatory foundation through the Data Governance Act and Data Act, which promote data altruism, create data intermediation services, and establish the European Data Innovation Board to develop cross-sectoral standards and ensure interoperability.

Roeingh identifies several critical legal challenges that must be addressed for CEDS to function effectively. These include clearly defining the rights, duties, and liability arrangements for all participants in these complex multi-stakeholder environments, particularly regarding intellectual property and personal data processing. The author draws parallels to physical infrastructure quality assurance, arguing that data spaces require robust mechanisms for validating, certifying, and auditing data quality through common standards, transparent governance structures, and continuous oversight.

The article continues by highlighting the particular importance of data quality standards when public sector bodies participate in CEDS, especially in areas like environment, public security, and energy. Since public bodies have binding obligations to uphold fundamental rights and must act on rational standards, poor-quality data can distort decision-making processes and violate the “garbage in, garbage out” principle. While the AI Act provides some guidance on data quality requirements for high-risk systems, Roeingh argues that concrete legal provisions specifically addressing data quality in data spaces are necessary, suggesting that statistical law frameworks could serve as useful models for developing these standards…

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