H4P-Connect is an interoperable middleware that acts as an intelligent bridge between different heterogeneous data sources (structured and unstructured), allowing their integration into a common ecosystem based on open standards and adapted to health, environmental and territorial environments.
H4P-Connect works as a plug&play integration layer for easy connection:
- Date lakes / Data warehouses
- Environmental sensor APIs (air, water, UV, etc.)
- Hospital and clinical systems (HL7, FHIR)
- Geospatial databases (GIS)
- Epidemiological surveillance networks
- Local government information systems
- Digital health and citizen well-being platforms
Format and delivery
Available as:
- Modular SaaS platform (private or public cloud).
- On-premise licence for environments with high privacy requirements.
- API-only version to integrate directly into existing solutions.
H4P-Connect aims to facilitate the interoperability, governance and exploitation of data so that any organisation (public or private) can:
- Consolidate information from different sources.
- Analyse it in an integrated way.
- Generate value through dashboards, AI or open APIs.
Value proposition
- Saves time and costs by removing interoperability barriers between disparate systems.
- Increases analytical accuracy through a holistic view of the health-environment-territory ecosystem.
- Empowers evidence-based decision making with consolidated, traceable and governed information.
Accelerates innovation by enabling AI and analytics teams to work with out-of-the-box data from multiple sources.
| Functionality |
Description |
| Universal connectivity |
Ready-to-use connectors (plug-ins) with standards such as HL7, FHIR, CSV, JSON, OGC, REST, SOAP, etc. |
| Semantic standardisation |
Homogenises and translates data using public health, environment, and climate ontologies. |
| Metadata management |
Module for cataloguing and traceability of data sources and data quality (Data Governance-ready). |
| Real-time intake |
Capability to receive and process continuous data streams from sensors, weather stations or satellite imagery. |
| Rules and events engine |
Define conditions (events) to trigger automatic actions (alerts, reporting, sending to apps). |
| Analytical sandbox |
Secure space for AI/data science teams with access to already integrated, anonymised and tagged data. |
| Geospatial compatibility |
Integration of coordinates, maps and GIS systems. Compatible with QGIS, ArcGIS, Mapbox, Google Maps, etc. |
| APIs for developers |
Expose normalised data as secure RESTful APIs (for mobile apps, reports, dashboards, etc.). |
| Security and legal compliance |
Compliant with RGPD, HIPAA and national regulations, with data encryption, access control and anonymisation. |
