About the FAIRness of Computable Biomedical Knowledge in Switzerland

Computable Biomedical Knowledge (CBK) refers to machine-readable and executable health information that supports automated, data-driven decision-making. It is critical for fast, automated decision-making in healthcare and must follow FAIR principles: Findable, Accessible, Interoperable, Reusable.

Switzerland’s Challenges include:

• A hypercompetitive academic culture limiting data sharing.
• Fragmented stakeholder landscape due to federalism and sectoral silos.
• Technical and legal complexities including lack of standards and regulatory diversity.
• Ethical concerns around data consent and commercial use.

Recommendations for making CBK FAIR:

• Systemic attribution mechanisms to credit researchers for data sharing.
• Collaboration between legal experts and researchers to navigate data laws.
• Technical standards and FAIRifications like RDF, SNOMED-CT, and HL7 FHIR.
• Robust ethical frameworks guided by national boards and international standards.

Implementation requires overcoming specific barriers, such as legal fragmentation, competitive research culture, and technical silos, while building on facilitators like open science practices, ongoing training initiatives, and Switzerland’s well-established bioinformatics infrastructure.

SLHS Lead: Université de Neuchâtel

Author: Abdessalam Ouaazki

Policy Brief: Download

Key Messages: Download

Summary Stakeholder Dialogue: Download