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European HPC cloud infrastructure for managing SARS-CoV-2 data in compliance with GDPR

 : The Connecting European SARS-CoV-2 Cohorts to Increase Common and Effective Response to SARS-CoV-2 Pandemic (ORCHESTRA) consortium, led by University of Verona (Italy), brings together key European academic experts and research institutions in infectious diseases, data management and High Perform...

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Autores principales: Dellacasa, C, Ortali, M, Rossi, E, D'Antonio, M, Osmo, T, Prasser, F, Puskaric, M, Rinaldi, E, Scipione, G
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9620090/
http://dx.doi.org/10.1093/eurpub/ckac129.427
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author Dellacasa, C
Ortali, M
Rossi, E
D'Antonio, M
Osmo, T
Prasser, F
Puskaric, M
Rinaldi, E
Scipione, G
author_facet Dellacasa, C
Ortali, M
Rossi, E
D'Antonio, M
Osmo, T
Prasser, F
Puskaric, M
Rinaldi, E
Scipione, G
author_sort Dellacasa, C
collection PubMed
description  : The Connecting European SARS-CoV-2 Cohorts to Increase Common and Effective Response to SARS-CoV-2 Pandemic (ORCHESTRA) consortium, led by University of Verona (Italy), brings together key European academic experts and research institutions in infectious diseases, data management and High Performance Computing (HPC) from 26 organizations (extending to 37 partners) from 15 countries. The project aims to create a new pan-European cohort built on existing and new large-scale population cohorts in European and non-European countries to significantly impact on the responsiveness to SARS-CoV-2. The integration and analysis of the very heterogeneous characteristics of SARS-CoV-2 data coming from many different sources such as EHR, retrospective and prospective patient registries, and related ‘omics’ data (incl. genomics, proteomics and transcriptomics) can benefit of data analytics enabled by HPC, where both high compute performance and fast storage capabilities are immensely important. During the first year of the project, a dedicated HPC cloud infrastructure have been designed and partially deployed to fulfill the functional requirements for data management ensuring healthcare data confidentiality/privacy, integrity and security in compliance with the European GDPR regulations. The result is an infrastructure for Data Management composed by three main layers: National Data Providers; National Hubs (one for each HPC center involved: CINECA - Italy, CINES - France and HLRS - Germany), to centralize data at national level and to support data storage, sharing and analysis on data ingested from the National Data Providers; ORCHESTRA Data Portal: the pan-European portal for sharing aggregated data and results. Currently data collection is on going; at the end of the project, clinical centers are expected to have enrolled more than 10.000 patients with about 50.000 samples for the prospective studies. KEY MESSAGES: • The SARS-CoV-2 crisis made evident the need to manage and analyse very heterogeneous health data coming from many different resources across different countries. • The HPC cloud infrastructure released for the Orchestra project can act as a model to manage future public health threats.
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spelling pubmed-96200902022-11-04 European HPC cloud infrastructure for managing SARS-CoV-2 data in compliance with GDPR Dellacasa, C Ortali, M Rossi, E D'Antonio, M Osmo, T Prasser, F Puskaric, M Rinaldi, E Scipione, G Eur J Public Health Parallel Programme  : The Connecting European SARS-CoV-2 Cohorts to Increase Common and Effective Response to SARS-CoV-2 Pandemic (ORCHESTRA) consortium, led by University of Verona (Italy), brings together key European academic experts and research institutions in infectious diseases, data management and High Performance Computing (HPC) from 26 organizations (extending to 37 partners) from 15 countries. The project aims to create a new pan-European cohort built on existing and new large-scale population cohorts in European and non-European countries to significantly impact on the responsiveness to SARS-CoV-2. The integration and analysis of the very heterogeneous characteristics of SARS-CoV-2 data coming from many different sources such as EHR, retrospective and prospective patient registries, and related ‘omics’ data (incl. genomics, proteomics and transcriptomics) can benefit of data analytics enabled by HPC, where both high compute performance and fast storage capabilities are immensely important. During the first year of the project, a dedicated HPC cloud infrastructure have been designed and partially deployed to fulfill the functional requirements for data management ensuring healthcare data confidentiality/privacy, integrity and security in compliance with the European GDPR regulations. The result is an infrastructure for Data Management composed by three main layers: National Data Providers; National Hubs (one for each HPC center involved: CINECA - Italy, CINES - France and HLRS - Germany), to centralize data at national level and to support data storage, sharing and analysis on data ingested from the National Data Providers; ORCHESTRA Data Portal: the pan-European portal for sharing aggregated data and results. Currently data collection is on going; at the end of the project, clinical centers are expected to have enrolled more than 10.000 patients with about 50.000 samples for the prospective studies. KEY MESSAGES: • The SARS-CoV-2 crisis made evident the need to manage and analyse very heterogeneous health data coming from many different resources across different countries. • The HPC cloud infrastructure released for the Orchestra project can act as a model to manage future public health threats. Oxford University Press 2022-10-25 /pmc/articles/PMC9620090/ http://dx.doi.org/10.1093/eurpub/ckac129.427 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the European Public Health Association. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Parallel Programme
Dellacasa, C
Ortali, M
Rossi, E
D'Antonio, M
Osmo, T
Prasser, F
Puskaric, M
Rinaldi, E
Scipione, G
European HPC cloud infrastructure for managing SARS-CoV-2 data in compliance with GDPR
title European HPC cloud infrastructure for managing SARS-CoV-2 data in compliance with GDPR
title_full European HPC cloud infrastructure for managing SARS-CoV-2 data in compliance with GDPR
title_fullStr European HPC cloud infrastructure for managing SARS-CoV-2 data in compliance with GDPR
title_full_unstemmed European HPC cloud infrastructure for managing SARS-CoV-2 data in compliance with GDPR
title_short European HPC cloud infrastructure for managing SARS-CoV-2 data in compliance with GDPR
title_sort european hpc cloud infrastructure for managing sars-cov-2 data in compliance with gdpr
topic Parallel Programme
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9620090/
http://dx.doi.org/10.1093/eurpub/ckac129.427
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