Trusted Research Environments (TRE): removing technical and governance barriers to support innovation and interdisciplinary research

可信研究环境（TRE）：消除技术和治理障碍以支持创新和跨学科研究

• 批准号: MC_PC_21029
• 负责人: Nicholas Mills
• 金额: $ 13.73万
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Intramural
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MC_PC_21029
• 关键词: Trusted; Research; Environments; TRE; removing

The project will be led by the DataLoch team at the University of Edinburgh, in collaboration with Public Health Scotland (PHS). DataLoch is a data service that curates health and social care data for 1.6m people in South-East Scotland. Approved applicants receive de-identified data extracts via the National Safe Haven - a Trusted Research Environment (TRE) managed by PHS Electronic Data Research and Innovation Service (eDRIS). However, this TRE was designed primarily for clinical or academic researchers, using traditional statistical software. It does not cater for other ‘non-traditional’ researchers or innovators from different disciplines, including software developers, experts in artificial intelligence (AI) or those from third- and private-sector organisations.This project will explore barriers to the use of TREs by non-traditional researchers from different disciplines and will deliver a prototype solution and user training module for DataLoch operating alongside the National Safe Haven. We will then produce a lessons learned report with recommendations for TREs across the United Kingdom, based on the following questions:1. What is expected from non-traditional TRE users to be considered trustworthy and credible? What public concerns exist about their use of TREs? What user accreditation standards are required?2. What additional technical security is required from a TRE to support research and innovation projects from different disciplines or organisations?3. What additional information governance is required to support TRE access from non-traditional researchers?

该项目将由爱丁堡大学的DataLoch团队领导，与苏格兰公共卫生(PHS)合作。DataLoch是一家数据服务公司，负责管理苏格兰东南部160万人的健康和社会保障数据。获得批准的申请者通过国家安全避风港-由PHS电子数据研究和创新服务(EDRIS)管理的可信研究环境(TRE)-获得去身份数据摘录。然而，这一TRE主要是为临床或学术研究人员设计的，使用的是传统的统计软件。它不迎合来自不同学科的其他非传统研究人员或创新者，包括软件开发人员、人工智能(AI)专家或来自第三和私营部门组织的那些人。该项目将探索来自不同学科的非传统研究人员使用TRES的障碍，并将为与国家安全避风港一起运行的DataLoch提供原型解决方案和用户培训模块。然后，我们将编写一份经验教训报告，根据以下问题为英国各地的TRE提出建议：1.非传统TRE用户被认为值得信赖和可信的期望是什么？公众对他们使用TRES有哪些担忧？需要哪些用户认证标准？2.为了支持来自不同学科或组织的研究和创新项目，TRE需要哪些额外的技术安全？3.需要哪些额外的信息治理来支持非传统研究人员的TRE访问？

项目成果

Governance Recommendations for Non-Traditional Researchers in Trusted Research Environments (TREs)

针对可信研究环境 (TRE) 中非传统研究人员的治理建议

• DOI: 10.5281/zenodo.7085517
• 发表时间: 2022
• 作者: Mills P