Implementation of an interoperable pan-European federated repository of health images, including secure data sharing mechanisms

An Interoperable pan-European federated repository of health images that allows sharing data in compliance with legal, ethical, privacy and security requirements, for AI-related training and experimentation; the repository will rely on federated data storage and will operated on a Federated Learning basis, abiding to the highest data privacy and security standards. It will also offer High Performance Computing-as-a-service, where necessary, thereby allowing for cost-effective performance of computationally intensive processing without the need for maintaining expensive equipment.


Interested in sharing health images to contribute to INCISIVE’s repository? Register your interest and we’ll be in touch with more details.


The following objectives will be implemented:

  • To incorporate a federated data storage schema: enabling the data providers to keep full control of their data, ensure their autonomy and at the same time contribute to the platform.

  • To implement a secure data exchange/sharing and privacy mechanism: based on blockchain technology and eIDAS, enabling secure access to data and identity management and ensuring trust.

  • To develop an automated data curation and an ML-based annotation service: ensuring high- data quality, correct interpretation of data/results, increasing speed and efficiency of annotation by minimizing the human intervention.

  • To incorporate a transaction tracking mechanism: based on blockchain technology recording the INCISIVE data transactions, ensuring transparency and traceability.

  • To define and implement a data donorship mechanism: following all related legal directives and enabling users to share their data while keeping full control of it.

  • To incorporate a data anonymization mechanism: enabling data processing, with respect to all related legal and ethical aspects. The mechanism will be bi-directional, including also a de-anonymization process.

  • To implement an interoperable data integration service: based on a common data model and well-established standards (HL7 FHIR, DICOM, SNOMED), enabling data providers to easily link their data sources to the INCISIVE platform.