D1.1 - Data Resources Map
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Description
The complex nature of cancer requires integration of advanced research data across national
boundaries to enable progress in prevention of cancer and the development of optimal
medical care. The European mission board for cancer has identified access to data,
knowledge and digital services across European borders vital for the cancer mission. The
goal in EOSC4Cancer is to make cancer-related genomic, imaging, clinical, environmental and
socio-economics data accessible through the use and improvement of existing federated
and interoperable systems. These systems will provide an infrastructure to securely identify,
share, process and reuse FAIR cancer data across borders. EOSC4Cancer use-cases will
cover the patient journey from cancer prevention to diagnosis and treatment, laying the
foundation of data trajectories and workflows for future cancer research projects. Curated
and FAIR datasets will be essential for advanced analytics and computational methods,
including machine learning, to be reproducible and robust.
The complex nature of cancer requires integration of advanced research data across national
boundaries to enable progress in prevention of cancer and the development of optimal
medical care. The European mission board for cancer has identified access to data,
knowledge and digital services across European borders vital for the cancer mission. The
goal in EOSC4Cancer is to make cancer-related genomic, imaging, clinical, environmental and
socio-economics data accessible through the use and improvement of existing federated
and interoperable systems. These systems will provide an infrastructure to securely identify,
share, process and reuse FAIR cancer data across borders. EOSC4Cancer use-cases will
cover the patient journey from cancer prevention to diagnosis and treatment, laying the
foundation of data trajectories and workflows for future cancer research projects. Curated
and FAIR datasets will be essential for advanced analytics and computational methods,
including machine learning, to be reproducible and robust.
Files
D1.1 Data Resources Map v1.0 - Final version.pdf
Files
(3.8 MB)
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