Architecture

Interactive diagrams of the Health Dataspace v2 architecture — 5-layer graph model, data flows, deployment topology, and identity trust framework.

5-Layer Knowledge Graph

The Neo4j knowledge graph organises health data across five architectural layers: DSP Marketplace (connector discovery), HealthDCAT-AP (dataset metadata), FHIR R4 (clinical data), OMOP CDM (research analytics), and Ontology (terminology alignment).

Fig 1. Five-layer knowledge graph architecture

Data Flow Pipeline

Synthetic patient data flows from Synthea generation through FHIR R4 resource loading into Neo4j, then transforms to OMOP CDM for research analytics. Each stage preserves full provenance through graph relationships.

Fig 2. End-to-end data flow from Synthea to analytics

Deployment Topology

The platform runs as Docker Compose services locally, with the Next.js UI also deployed as a static export to GitHub Pages for the demo site. The JAD infrastructure provides PostgreSQL, Keycloak SSO, Vault secrets, and NATS event mesh.

Fig 3. Deployment architecture and service topology

DSP Contract Negotiation

The Dataspace Protocol (DSP) governs how data holders and data users negotiate access to health datasets. The EHDS regulation adds HDAB approval as a pre-requisite for data permit issuance before contract negotiation can proceed.

Fig 4. DSP contract negotiation with EHDS compliance

Identity & Trust Framework

The Decentralized Claims Protocol (DCP) manages identity, credentials, and trust. Identity Hub stores DIDs and Verifiable Credentials, the Issuer Service mints EHDS-specific credentials, and Keycloak provides SSO/OIDC authentication.

Fig 5. DCP identity and trust architecture

Diagram Legend

■ Solid lines — direct data flow or API calls

■ Dashed lines — mapping / transformation relationships

● Subgraphs — logical boundary groupings

● Participants — protocol actors in sequence diagrams