PDF(Pubmed)
Abstract：
UNASSIGNED: The ORCHESTRA project, funded by the European Commission, aims to create a pan-European cohort built on existing and new large-scale population cohorts to help rapidly advance the knowledge related to the prevention of the SARS-CoV-2 infection and the management of COVID-19 and its long-term sequelae. The integration and analysis of the very heterogeneous health data pose the challenge of building an innovative technological infrastructure as the foundation of a dedicated framework for data management that should address the regulatory requirements such as the General Data Protection Regulation (GDPR).
UNASSIGNED: The three participating Supercomputing European Centres (CINECA - Italy, CINES - France and HLRS - Germany) designed and deployed a dedicated infrastructure to fulfil the functional requirements for data management to ensure sensitive biomedical data confidentiality/privacy, integrity, and security. Besides the technological issues, many methodological aspects have been considered: Berlin Institute of Health (BIH), Charité provided its expertise both for data protection, information security, and data harmonisation/standardisation.
UNASSIGNED: The resulting infrastructure is based on a multi-layer approach that integrates several security measures to ensure data protection. A centralised Data Collection Platform has been established in the Italian National Hub while, for the use cases in which data sharing is not possible due to privacy restrictions, a distributed approach for Federated Analysis has been considered. A Data Portal is available as a centralised point of access for non-sensitive data and results, according to findability, accessibility, interoperability, and reusability (FAIR) data principles. This technological infrastructure has been used to support significative data exchange between population cohorts and to publish important scientific results related to SARS-CoV-2.
UNASSIGNED: Considering the increasing demand for data usage in accordance with the requirements of the GDPR regulations, the experience gained in the project and the infrastructure released for the ORCHESTRA project can act as a model to manage future public health threats. Other projects could benefit from the results achieved by ORCHESTRA by building upon the available standardisation of variables, design of the architecture, and process used for GDPR compliance.
UNASSIGNED: The three participating Supercomputing European Centres (CINECA - Italy, CINES - France and HLRS - Germany) designed and deployed a dedicated infrastructure to fulfil the functional requirements for data management to ensure sensitive biomedical data confidentiality/privacy, integrity, and security. Besides the technological issues, many methodological aspects have been considered: Berlin Institute of Health (BIH), Charité provided its expertise both for data protection, information security, and data harmonisation/standardisation.
UNASSIGNED: The resulting infrastructure is based on a multi-layer approach that integrates several security measures to ensure data protection. A centralised Data Collection Platform has been established in the Italian National Hub while, for the use cases in which data sharing is not possible due to privacy restrictions, a distributed approach for Federated Analysis has been considered. A Data Portal is available as a centralised point of access for non-sensitive data and results, according to findability, accessibility, interoperability, and reusability (FAIR) data principles. This technological infrastructure has been used to support significative data exchange between population cohorts and to publish important scientific results related to SARS-CoV-2.
UNASSIGNED: Considering the increasing demand for data usage in accordance with the requirements of the GDPR regulations, the experience gained in the project and the infrastructure released for the ORCHESTRA project can act as a model to manage future public health threats. Other projects could benefit from the results achieved by ORCHESTRA by building upon the available standardisation of variables, design of the architecture, and process used for GDPR compliance.
摘要：
■ORCHESTRA项目，由欧盟委员会资助，旨在建立一个建立在现有和新的大规模人群队列基础上的泛欧洲队列，以帮助快速推进与预防SARS-CoV-2感染和管理COVID-19及其长期后遗症相关的知识。非常异构的健康数据的集成和分析提出了构建创新技术基础设施作为数据管理专用框架的基础的挑战，该框架应满足诸如通用数据保护条例（GDPR）之类的监管要求。
■参与的三个超级计算欧洲中心（CINECA-意大利，CINES-法国和HLRS-德国）设计并部署了专用基础架构，以满足数据管理的功能要求，以确保敏感的生物医学数据机密性/隐私性，完整性，和安全。除了技术问题,已经考虑了许多方法方面：柏林卫生研究所(BIH)，Charité为数据保护提供了专业知识，信息安全,和数据协调/标准化。
■由此产生的基础架构基于多层方法，该方法集成了几种安全措施以确保数据保护。在意大利国家中心建立了一个集中的数据收集平台，同时，对于由于隐私限制而无法进行数据共享的用例，已经考虑了联合分析的分布式方法。数据门户可用作非敏感数据和结果的集中式访问点，根据可查找性，可访问性,互操作性，和可重用性(FAIR)数据原则。该技术基础设施已用于支持人群之间的重要数据交换，并发布与SARS-CoV-2相关的重要科学结果。
■考虑到根据GDPR法规的要求对数据使用的需求不断增加，在该项目中获得的经验和为ORCHESTRA项目发布的基础设施可以作为管理未来公共卫生威胁的模型。其他项目可以受益于ORCHESTRA通过建立现有的变量标准化所取得的成果，建筑设计，和用于GDPR合规性的流程。
■参与的三个超级计算欧洲中心（CINECA-意大利，CINES-法国和HLRS-德国）设计并部署了专用基础架构，以满足数据管理的功能要求，以确保敏感的生物医学数据机密性/隐私性，完整性，和安全。除了技术问题,已经考虑了许多方法方面：柏林卫生研究所(BIH)，Charité为数据保护提供了专业知识，信息安全,和数据协调/标准化。
■由此产生的基础架构基于多层方法，该方法集成了几种安全措施以确保数据保护。在意大利国家中心建立了一个集中的数据收集平台，同时，对于由于隐私限制而无法进行数据共享的用例，已经考虑了联合分析的分布式方法。数据门户可用作非敏感数据和结果的集中式访问点，根据可查找性，可访问性,互操作性，和可重用性(FAIR)数据原则。该技术基础设施已用于支持人群之间的重要数据交换，并发布与SARS-CoV-2相关的重要科学结果。
■考虑到根据GDPR法规的要求对数据使用的需求不断增加，在该项目中获得的经验和为ORCHESTRA项目发布的基础设施可以作为管理未来公共卫生威胁的模型。其他项目可以受益于ORCHESTRA通过建立现有的变量标准化所取得的成果，建筑设计，和用于GDPR合规性的流程。
