Layered Approach
Data spaces are multi-layered ecosystems that rely on the seamless integration of technical protocols, business processes, and legal frameworks. One of the foundational challenges in governing data spaces lies in the consistent definition and use of key concepts such as "roles," "policies," and "contracts." These terms often carry different meanings across domains. This chapter establishes a clear separation between technical and non-technical interpretations of such concepts to support the development of interoperable and trustworthy data spaces.
Layers of a Data Space
Data spaces can be structured into three primary layers, each serving distinct functions:
Technical Layer – Encompasses the architecture and protocols (e.g., Dataspace Protocol (DSP), Decentralized Claims Protocol (DCP)) that facilitate secure and interoperable data exchanges.
Economic Layer – Manages the services, interactions, and workflows that enable value generation and marketplace activity. Notably, terms for this layer are also Business or Operational Layer.
Legal and Governance Layer – Enforces rights, obligations, and regulatory compliance across participants.
These layers interact but must be conceptually separated to ensure clarity and reduce ambiguity in roles and responsibilities.
Clarifying the Concept of Roles
The term "role" is context-dependent and must be clearly scoped:
At the technical level, there is only one fundamental role: participant. A participant acts as a data provider, a data consumer, or both within the data exchange protocol.
At the business level, participants may take roles such as data intermediary, marketplace operator, auditor, or service provider.
These business roles do not exist independently at the technical layer but are mapped onto the core participant role based on the services performed.
Maintaining this distinction ensures that governance models remain technically sound while accommodating diverse business scenarios.
Distinguishing Data Spaces from Trusted Data Transactions
A clear differentiation must be made between data spaces and trusted data transactions (TDTs):
Data spaces are decentralized infrastructures that enable sovereign data exchange based on open standards. They preserve participant autonomy and operate without mandatory intermediaries.
Trusted data transactions, as under current standardization in the European Commission's Standardization Request on a Trusted Data Framework in CEN/CENELEC JTC 25, can also be associated with the EU Data Governance Act. They can also be related to data intermediaries and service orchestration. Such models prioritize regulatory alignment and controlled environments.
While trusted data transactions may operate within data spaces, they are conceptually distinct. Equating them risks narrowing the scope of data space implementations and excluding more decentralized or peer-to-peer configurations.
Participation and Representation
Participants in a data space are defined by their ability to exchange data via technical protocols. This has several implications:
Organizations, not individuals, are considered technical participants. These organizations are represented by software agents capable of executing data space protocols.
Natural persons interact with data spaces indirectly through applications or services operated by organizations.
Trust anchors, identity providers, and regulators may influence data transactions but do not participate directly unless they act through technical interfaces governed by data space rules.
This model preserves the integrity of technical interactions while allowing flexibility in higher layers.
The Role of External Actors
Entities that provide static resources—such as ontologies, schemas, or public credentials—may support the data space but are not considered participants unless they actively engage via governed interfaces. For example:
A web service that hosts a data sharing ontology is not a participant but serves as an external reference.
A trust framework provider may act as a participant if it delivers services subject to data space governance policies.
Participation requires governance commitment and technical integration.
Implications for the Rulebook
The Rulebook should reflect these principles clearly:
The only technical role is the participant, which may act as data provider, consumer, or both.
Business roles are supplementary and must be defined within the business or legal governance layers.
Visual representations of data space structures must be clearly labeled to indicate whether they depict technical, business, or legal perspectives.
Such clarity supports interoperability, ensures accurate alignment with regulatory frameworks, and promotes broad adoption across sectors.
Overview on roles and Layers
In line with the description of the role models and the layered approach, the diagram below presents an overview on roles in data spaces and their affilation to the layers.
This diagram is a foundation to depict the typical use cases of the roles in relation to data spaces.
Conclusion
Effective data space governance depends on the precise use of terminology and clear separation of concerns across layers. Establishing the participant as the core technical role, while accommodating richer business and regulatory interactions above it, ensures a scalable and interoperable foundation. This layered perspective will guide the elaboration of rules, responsibilities, and interactions in subsequent chapters of the Rulebook.
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