Imagine if every hospital in Europe kept their cancer records in a different language and format; finding a pattern would be impossible. This project builds a digital bridge that lets researchers securely search and analyze these different records in one place. It's like creating a universal translator and a shared library for medical data so doctors can find the best treatments faster.
Cancer research is slowed down because clinical, genomic, and imaging data are trapped in isolated silos across different countries. This prevents the use of AI and machine learning which require massive, standardized datasets to find new treatment patterns.
A federated data infrastructure including a living map of data resources, a portable cBioPortal for multi-type data integration, and a cancer-specific FAIR data guidance page in RDMkit.
If you are a drug discovery firm dealing with fragmented patient data across borders — this project developed interoperable workflows and a living map of data resources that speeds up the identification of patient cohorts for clinical trials.
If you are a medical software provider dealing with incompatible imaging and genomic data formats — this project developed a portable cBioPortal implementation that integrates multiple federated data types into one view.
If you are a private oncology clinic dealing with the difficulty of comparing local patient results with global research — this project developed analysis workflows and FAIR data protocols that make clinical data reusable and comparable.
Based on available project data, the project was funded by a EUR 7,814,549 EU contribution, but specific commercial pricing for end-users is not listed.
Yes, the project is built on the European Open Science Cloud (EOSC) and involves 36 partners across 13 countries, indicating a design meant for pan-European scale.
Based on available project data, the project emphasizes FAIR data practices and publicly available best practices, suggesting an open-access or open-science licensing model.
The project focuses on a privacy-aware, federated data ecosystem to ensure secure identification and sharing of clinical and molecular data across borders.
The project developed demonstrators for interoperability across data resources and portals, specifically extending tools like cBioPortal to link with other platforms.
The consortium is heavily weighted toward research and academic excellence, featuring 22 research organizations and 10 universities. While industry representation is low at 3% (only 1 industry partner and 2 SMEs), the presence of the Barcelona Supercomputing Center as coordinator ensures high-performance computing capabilities. The 13-country spread indicates a strong capacity for cross-border data standardization.
Contact the Barcelona Supercomputing Center (BSC) regarding the EOSC4Cancer infrastructure
Contact SciTransfer to find partners for implementing these FAIR oncology data standards in your pipeline.
