Observatory for Monitoring Data-Driven Approaches to Covid-19 ("OMDDAC")
Covid-19 数据驱动方法监测观察站(“OMDDAC”)
基本信息
- 批准号:AH/V012789/1
- 负责人:
- 金额:$ 41.79万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Research Grant
- 财政年份:2020
- 资助国家:英国
- 起止时间:2020 至 无数据
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
OMDDAC will provide a national, public space for the consolidation of knowledge and understanding around data-driven approaches to COVID-19, focused upon legal, ethical, policy and operational challenges. Data-driven responses are being developed rapidly across the public sector, academia and industry. These include combining digital health datasets within a single dashboard, use of communications data to map trends, monitoring of quarantine behaviour by drones and automated number plate recognition, and access to Bluetooth data for contact tracing. Developing technology in a 'one-dimensional' way (Nuffield Council on Bioethics 2020) without appropriate consideration of underlying values and judgements, the context and resulting interventions brings with it a high risk of errors, limited efficacy and unintended consequences for individuals. OMDACC's purpose is to provide a long-term mechanism to mitigate these risks in a way that responds to public opinion. This will be achieved by adopting an innovative mixed-methods research design, incorporating case study analysis, stakeholder interviews, representative public surveys, and the development of practitioner-focussed guidelines.By collating lessons learned throughout this period, OMDDAC will be integral to informing both policy and public thinking regarding pandemic management. It is imperative that the UK develops a framework governing the use of data-driven approaches that can be deployed during public health emergencies. Drawing on a powerful range of practical and academic expertise, and working with influential supporting partners such as the Ada Lovelace Institute, OMDDAC is designed to facilitate this process.
OMDDAC将提供一个全国性的公共空间,以巩固对COVID-19数据驱动方法的知识和理解,重点关注法律的、道德、政策和运营挑战。公共部门、学术界和工业界正在迅速制定数据驱动的应对措施。其中包括将数字健康数据集结合在一个仪表板中,使用通信数据来绘制趋势图,通过无人机和自动车牌识别来监测检疫行为,以及访问蓝牙数据以进行接触追踪。以“一维”方式开发技术(纳菲尔德生物伦理理事会,2020年),而不适当考虑基本价值观和判断,背景和由此产生的干预措施,带来了很高的风险错误,有限的效力和对个人的意外后果。OMDACC的目的是提供一个长期机制,以应对公众舆论的方式减轻这些风险。这将通过采用创新的混合方法研究设计来实现,包括案例研究分析、利益相关者访谈、代表性公众调查和制定以预防为重点的指南。通过整理在此期间吸取的经验教训,OMDDAC将成为为流行病管理方面的政策和公众思维提供信息的不可或缺的组成部分。联合王国必须制定一个框架,管理在公共卫生紧急情况下使用数据驱动方法的情况。利用强大的实践和学术专业知识,并与Ada Lovelace Institute等有影响力的支持合作伙伴合作,OMDDAC旨在促进这一过程。
项目成果
期刊论文数量(8)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Children, Public Sector Data-Driven Decision-Making and Article 12 UNCRC
儿童、公共部门数据驱动决策和 UNCRC 第 12 条
- DOI:
- 发表时间:2022
- 期刊:
- 影响因子:0
- 作者:Claire Bessant
- 通讯作者:Claire Bessant
OMDDAC Snapshot Report 1: Data-Driven Public Policy
OMDDAC 快照报告 1:数据驱动的公共政策
- DOI:
- 发表时间:2021
- 期刊:
- 影响因子:0
- 作者:Allsopp R.
- 通讯作者:Allsopp R.
Observing Data-Driven Approaches to Covid-19: Reflections from a Distributed, Remote, Interdisciplinary Research Project
观察数据驱动的 Covid-19 方法:分布式、远程、跨学科研究项目的反思
- DOI:
- 发表时间:2021
- 期刊:
- 影响因子:0
- 作者:Allsopp R.
- 通讯作者:Allsopp R.
Data-Driven Responses to COVID-19: Lessons Learned: OMDDAC Research Compendium
针对 COVID-19 的数据驱动响应:经验教训:OMDDAC 研究纲要
- DOI:
- 发表时间:2021
- 期刊:
- 影响因子:0
- 作者:Allsopp R.
- 通讯作者:Allsopp R.
OMDDAC Snapshot Report 4: Survey of Public Perceptions of Data-Sharing for COVID-19 Related Purposes
OMDDAC 快照报告 4:公众对 COVID-19 相关目的数据共享的看法调查
- DOI:
- 发表时间:2021
- 期刊:
- 影响因子:0
- 作者:Sutton S.
- 通讯作者:Sutton S.
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Marion Oswald其他文献
Membrane computing and brain modelling
- DOI:
10.1007/s10015-008-0619-0 - 发表时间:
2009-03 - 期刊:
- 影响因子:0.9
- 作者:
Marion Oswald - 通讯作者:
Marion Oswald
P systems with local graph productions
- DOI:
10.1007/bf03037287 - 发表时间:
2004-12-01 - 期刊:
- 影响因子:2.800
- 作者:
Rudolf Freund;Marion Oswald - 通讯作者:
Marion Oswald
Independent agents in a globalized world modelled by tissue P systems
- DOI:
10.1007/s10015-007-0424-1 - 发表时间:
2007-07 - 期刊:
- 影响因子:0.9
- 作者:
Marion Oswald - 通讯作者:
Marion Oswald
Array Insertion and Deletion P Systems
数组插入和删除 P 系统
- DOI:
10.1007/978-3-642-39074-6_8 - 发表时间:
2013 - 期刊:
- 影响因子:0
- 作者:
H. Fernau;R. Freund;Sergiu Ivanov;Marion Oswald;Markus L. Schmid;K. Subramanian - 通讯作者:
K. Subramanian
Exploring Police Perspectives on Algorithmic Transparency: A Qualitative Analysis of Police Interviews in the UK
探索警方对算法透明度的看法:英国警方访谈的定性分析
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Miri Zilka;Carolyn Ashurst;Luke Chambers;Ellen P Goodmann;Pamela Ugwudike;Marion Oswald - 通讯作者:
Marion Oswald
Marion Oswald的其他文献
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{{ truncateString('Marion Oswald', 18)}}的其他基金
"Ethical Review to Support Responsible AI in Policing - A Preliminary Study of West Midlands Police's Specialist Data Ethics Review Committee "
“支持警务中负责任的人工智能的道德审查——西米德兰兹郡警察专家数据道德审查委员会的初步研究”
- 批准号:
AH/Z505626/1 - 财政年份:2024
- 资助金额:
$ 41.79万 - 项目类别:
Research Grant
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