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团队与苏格兰公共卫生部（PHS）合作领导。DataLoch是一项数据服务，为苏格兰东南部160万人提供健康和社会保健数据。批准的申请人通过国家安全港接收去识别数据提取-一个由PHS电子数据研究和创新服务（eDRIS）管理的可信研究环境（TRE）。然而，这个TRE主要是为临床或学术研究人员设计的，使用传统的统计软件。该项目不面向其他来自不同学科的“非传统”研究人员或创新者，包括软件开发人员、人工智能（AI）专家或来自第三方和私营机构的人员。该项目将探讨来自不同学科的非传统研究人员使用TREs的障碍，并将为DataLoch提供一个原型解决方案和用户培训模块。然后，我们将根据以下问题编写一份经验教训报告，并为英国各地的TREs提出建议：1。对非传统TRE用户的期望是什么？公众对他们使用TREs有哪些担忧？需要什么样的用户认证标准？2.为了支持来自不同学科或组织的研究和创新项目，TRE还需要什么额外的技术安全？3.为了支持非传统研究人员获取TRE，还需要哪些额外的信息管理？

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