On Distributed Collaboration for Biomedical Analyses

Cooperation of research groups is nowadays common for the development and execution of biomedical analyses. Multiple partners contribute data in this context, data that is often centralized for processing at some cluster-based or supercomputer-based infrastructure. In contrast, real distributed coll...

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Autores:
Boujdad, Fatima-Zahra
Gaignard, Alban
Südholt, Mario
Garzón-Alfonso, Wilmer
Benavides Navarro, Luis Daniel
Redon, Richard
Tipo de recurso:
Documento de conferencia en no proceso
Fecha de publicación:
2019
Institución:
Escuela Colombiana de Ingeniería Julio Garavito
Repositorio:
Repositorio Institucional ECI
Idioma:
eng
OAI Identifier:
oai:repositorio.escuelaing.edu.co:001/1797
Acceso en línea:
https://repositorio.escuelaing.edu.co/handle/001/1797
Palabra clave:
data privacy
distributed databases
groupware
medical administrative data processing
medical computing
Arquitectura de computadores
Protección de datos
Procesamiento electrónico de datos
Bioinformática
Computer architecture
Collaboration
Genetics
Bioinformatics
Cloud computing
Hospitals
Security
Rights
closedAccess
License
https://creativecommons.org/licenses/by/4.0/
Description
Summary:Cooperation of research groups is nowadays common for the development and execution of biomedical analyses. Multiple partners contribute data in this context, data that is often centralized for processing at some cluster-based or supercomputer-based infrastructure. In contrast, real distributed collaboration that involves processing of data from several partners at different sites is rare. However, such distributed analyses are often very interesting, in particular, for scalability, security and privacy reasons. In this article, we motivate the need for real distributed biomedical analyses in the context of several ongoing projects, including the ICAN project that involves 34 French hospitals and affiliated research groups. We present a set of distributed architectures for such analyses that we have derived from discussions with different medical research groups and a study of related work. These architectures allow for scalability, security/privacy and reproducibility issues to be taken into account. Finally, we illustrate that these architectures can serve as the basis of a development method for biomedical distributed analyses.