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ZENODO
Other literature type . 2023
License: CC BY
Data sources: ZENODO
ZENODO
Project deliverable . 2023
License: CC BY
Data sources: Datacite
ZENODO
Project deliverable . 2023
License: CC BY
Data sources: Datacite
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D1.1 - Data Resources Map

Authors: Swertz, Morris; Been, Gerieke; Hijmans, Brenda;

D1.1 - Data Resources Map

Abstract

The complex nature of cancer requires integration of advanced research data across nationalboundaries to enable progress in prevention of cancer and the development of optimalmedical care. The European mission board for cancer has identified access to data,knowledge and digital services across European borders vital for the cancer mission. Thegoal in EOSC4Cancer is to make cancer-related genomic, imaging, clinical, environmental andsocio-economics data accessible through the use and improvement of existing federatedand interoperable systems. These systems will provide an infrastructure to securely identify,share, process and reuse FAIR cancer data across borders. EOSC4Cancer use-cases willcover the patient journey from cancer prevention to diagnosis and treatment, laying thefoundation of data trajectories and workflows for future cancer research projects. Curatedand 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 nationalboundaries to enable progress in prevention of cancer and the development of optimalmedical care. The European mission board for cancer has identified access to data,knowledge and digital services across European borders vital for the cancer mission. Thegoal in EOSC4Cancer is to make cancer-related genomic, imaging, clinical, environmental andsocio-economics data accessible through the use and improvement of existing federatedand interoperable systems. These systems will provide an infrastructure to securely identify,share, process and reuse FAIR cancer data across borders. EOSC4Cancer use-cases willcover the patient journey from cancer prevention to diagnosis and treatment, laying thefoundation of data trajectories and workflows for future cancer research projects. Curatedand FAIR datasets will be essential for advanced analytics and computational methods,including machine learning, to be reproducible and robust.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
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