Output

In this section you will find the (links to the) output of our activities.

Discover

Landscape analysis

This involves the analysis of similar and related initiatives and models.

Cancer Image Europe (EUCAIM) hyper-ontology EUCAIM is pioneering a pan-European federated infrastructure for cancer images, fueling AI innovations. It addresses semantic interoperability challenges among distributed data repositories that use heterogeneous cancer image data models through a semantically well-founded domain ontology for the oncology domain. To enable federated querying across these repositories, the integration of a semantic interoperability layer is required. The so-called EUCAIM hyper-ontology is a common semantic meta-model that aims to support and maintain semantic interoperability among heterogeneous cancer image data models/standard. Using the hyper-ontology, the real-world meaning of essential medical and imaging data/metadata is preserved and exchanged in a standardized, consistent, and meaningful way. Its core layer and upper layer are based on the Unified Foundational Ontology (UFO) with links to HL7 minimal Common Oncology Data Elements (mCODE).

ERDERA CARE-SM

KIK-V

Simple Standard for Sharing Ontological Mappings (SSSOM)

Yosemite project

Common Data Models in GDI, cohorts, oncology domain node, and HealthAI

European Data Spaces

Initial use case selection

Define

Personas and user journeys

Develop & Deliver

All versions of the reference model will be made openly available to the community via the repository at https://w3id.org/health-ri/semantic-interoperability.