Technical

data spaces

Decentralised, standards-based environments for cross-domain data sharing.

How the laws define this

Regulators consistently define data spaces as secure, interoperable environments or governed ecosystems that enable cross-sector dataset sharing and reuse under defined technical and legal rules. Whether operating across organizations or borders, these arrangements ensure data exchange remains controlled, compliant, and standardized without compromising data sovereignty or legal protection. Definitions diverge primarily regarding operational scope and specific technical functions. The Turkey National AI Strategy 2021-2025 explicitly incorporates data storage, dataset annotation standards, and AI model training directly into its framework. In contrast, the Datenstrategie für Österreich (Data Strategy for Austria) and the Data Strategy of the Federal Government ('Datenstrategie der Bundesregierung') emphasize decentralised or federated architectures focused on multi-sectoral data exchange. Meanwhile, the Canada-EU Memorandum of Understanding on Artificial Intelligence highlights cross-jurisdictional transfers, whereas the Concept for the Development of Artificial Intelligence in Bulgaria until 2030 (National AI Strategy) links dataset exchange directly to open data policies and GDPR compliance.

Synthesised from the 5 statutory definitions below. Each one is quoted in full, with its source.

How jurisdictions differ

What is distinctive in each definition, binding law in force first. Showing 4 of the 5 instruments that define this term; all are listed under Definitions below.

Jurisdiction	Instrument	Status	What is distinctive
Canada	Canada-EU Memorandum of Understanding on Artificial Intelligence	In Force	Adds focus on cross-jurisdictional exchange between Canada and EU, including model-relevant information, under bilateral cooperation arrangements.
Austria	Data Strategy for Austria	Adopted	Emphasizes preservation of data sovereignty and legal compliance, with intent to support sectoral ecosystems and EU-level interoperability.
Germany	Data Strategy of the Federal Government	Adopted	Specifies federated environments as sectoral or cross-sectoral constructs with examples like industry, health, mobility, environment, and public administration.
Bulgaria	Concept for the Development of Artificial Intelligence in Bulgaria until 2030	Adopted	Limits to public and private datasets explicitly tied to AI development, open data policies, and sectoral uptake under GDPR compliance.

Definitions (5)

Decentralised environments structured by governance rules and shared technical standards that enable cross-domain, interoperable data exchange between organisations while preserving control, sovereignty and legal compliance; intended to support sectoral ecosystems and EU-level interoperability.

Datenstrategie für Österreich (Data Strategy for Austria)Definition 1 of 5

Interoperable, secure platforms and environments for storing, sharing, annotating and governing datasets to facilitate training and reuse of AI models. Data spaces in the Strategy include common annotation standards, access controls and data-sharing frameworks intended for public sector and multi‑stakeholder use.

Turkey National AI Strategy 2021-2025Definition 2 of 5

Governed ecosystems for data sharing that define legal, technical, and interoperability arrangements to enable secure, controlled exchange of datasets and model‑relevant information across organizations and jurisdictions.

Canada-EU Memorandum of Understanding on Artificial IntelligenceDefinition 3 of 5

Federated, standards-based environments that enable data sharing under defined governance arrangements, technical and semantic interoperability, and access rules across sectors or organisations. The Strategy describes them as sectoral or cross-sectoral constructs (e.g., industry, health, mobility, environment, public administration) to facilitate secure, governed data exchange and reuse.

Data Strategy of the Federal Government ('Datenstrategie der Bundesregierung')Definition 4 of 5

Interoperable and secure data‑sharing infrastructures and associated policies intended to enable access to, exchange of and reuse of public and private datasets across sectors while ensuring compliance with data protection rules (e.g., GDPR), supporting open data policies and facilitating AI development and sectoral uptake.

Concept for the Development of Artificial Intelligence in Bulgaria until 2030 (National AI Strategy)Definition 5 of 5

Not to be confused with

National data spaces

National data spaces refer to structured repositories limited to public and research data reuse, while data spaces are broader governed environments for cross-domain sharing.

data infrastructure

Data infrastructure covers technical platforms and processing environments, whereas data spaces include governance, standards, and interoperability arrangements.

Questions and answers

What makes data spaces in the Canada-EU AI MOU different?

It defines data spaces as governed ecosystems enabling secure exchange across organizations and jurisdictions, specifically between Canada and the EU. This includes model-relevant information alongside datasets. The focus is on bilateral trustworthy AI cooperation.

How does Germany's Data Strategy describe data spaces?

They are federated, standards-based environments for data sharing across defined sectors like health or mobility. The strategy promotes secure, governed exchange and reuse through technical and semantic interoperability.

Are data spaces in national strategies legally binding?

No, all listed definitions come from policies or strategies marked as NOT BINDING. They guide data governance but impose no legal duties.