Fundamentals
What is a data space?
A data space is a federated technical infrastructure that enables the exchange of data between heterogeneous systems in a secure and controlled manner. It provides the necessary components for interoperability, data governance, and the application of usage policies, allowing on-demand access and processing without the need to centralize or replicate information.
Publication of data
Criteria for organizing and publishing data
The organization and publication of data in the data space is governed by principles of quality, consistency, traceability, and control by providers, with the aim of ensuring reliable, transparent exchange that is aligned with the technical and regulatory requirements of each sector. In this context, each piece of published data must meet the following criteria:
Have a clearly identified issuer with verifiable credentials (VC).
Include a description of the data schema, the unit of measurement, and its purpose.
Clearly specify the associated terms of use.
Explicitly define the data access mode: real-time, per event, or on demand.
Our solutions
Description and control of data sets
Each shared dataset includes the information necessary to ensure its correct understanding, use, and interoperability among participants in the data space, while always maintaining the provider’s sovereignty over their data. Specifically, each dataset includes:
Common semantics
A semantic description based on ontologies and sector-specific taxonomies.
Context metadata
Metadata with information about the origin of the data, its format, and the frequency of updates.
Policies on use and access
Associated usage policies, expressed through a digital contract that details who can access the data, for what purposes and under what conditions, and for how long.
Access at source
A source access model, with no historical data storage by the platform, allowing each provider to decide what data to share and for how long.
Key features
Alignment with European initiatives, standards, and frameworks
Data Spaces Support Center (DSSC) and Data Space Business Alliance (DSBA) as conceptual, technical, and organizational reference frameworks for European data spaces.
Alignment with European initiatives, standards, and frameworks
- Gaia-X as a trusted framework and federated architecture for sovereign data exchange.
- International Data Spaces Association (IDSA) and its Reference Architecture Model (IDS-RAM) for defining roles, components, and data exchange flows.
- W3C through standards such as ODRL for defining usage policies and data contracts.
- DCAT-AP as a European profile for the description and cataloging of datasets.
- European initiatives and platforms developed under the Digital Europe program, aimed at facilitating the technical adoption of data spaces.
CONFIDENCE
Trusted environment: control, traceability, and legal and organizational frameworks
Trust among participants is established through a set of mechanisms that ensure authenticity, control, and traceability in all data exchange operations. This approach allows each actor to maintain sovereignty over their data, while ensuring security and compliance with defined policies. The key elements of the framework are:
Verifiable identities (DID/VC) that guarantee the authenticity of participating entities and individuals.
Attribute-based authentication and authorization (ABAC) mechanisms to control access based on specific roles and characteristics.
Certification of participants and automatic validation of credentials to ensure the reliability of actors.
Complete recording and traceability of each operation performed, enabling audits and accurate monitoring.
Real-time policy engine that evaluates each data access and verifies compliance with the conditions defined for each transaction.
RULES OF USE
Governance and ethics
The governance model combines mandatory rules and flexible agreements to ensure a secure, transparent operating framework that is aligned with European principles of sovereignty and fairness in data use.
Governance
- Hard Law: Common rules based on European principles.
- Soft Law: Contractual agreements between participants
Ethics
- Usage control
- Full traceability
- Revocation of access
- Best practices and active participation
TECHNICAL ARCHITECTURE
Technical architecture and data space integration model
The data space architecture is based on the DSBA model and is designed to offer interoperability, security, and scalability in multi-sector environments. It combines components, standards, and protocols that enable the flexible integration and deployment of services:
Each vendor manages its own assets through customized catalogs, publication flows and access control. Data is transformed into common models, such as NGSI-LD, to ensure interoperability. Sharing is governed by digital contracts, dynamically evaluated by policy engines (OPA), with integrated traceability and auditing.
Data remains hosted on the provider’s infrastructure, whether in edge, cloud or hybrid systems. The platform does not centralize information, but acts as an intermediary to discover, access and consume data directly at its original location, through secure and auditable connectors.
The primary responsibility lies with the provider, but the ecosystem includes mechanisms for semantic validation, traceability, versioning and origin certification that strengthen trust. Furthermore, data contracts allow explicit conditions to be established regarding the use, format, frequency or quality of the shared information.
Access is enabled for organizations registered as participants, which can assume roles of provider, consumer or operator/customer. Each access is governed by verifiable credentials and digitally signed usage contracts. Governance policies allow access to be restricted based on context, type of consumer, stated purpose or level of trust required.
