Public involvement in big data projects: an ethnographically-informed study.

IF 1.6 Q3 HEALTH CARE SCIENCES & SERVICES International Journal of Population Data Science Pub Date : 2022-08-25 DOI:10.23889/ijpds.v7i3.1991
Elisa Jones, L. Frith, A. Chiumento, S. Rodgers, Alan Clarke, S. Markham
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Abstract

ObjectivesPublic involvement and engagement (PIE)) is playing an increasingly important role in big data initiatives and projects. It is therefore important to gain a deeper understanding of the different approaches used. ApproachThis study explores PIE using ethnographically-informed qualitative case studies. The case studies include: three citizen juries, each one carried out over eight days and that asked jurors to consider different real-world health data initiatives; and a public panel set up by a regional databank that carries out data linking. Data collection is ongoing and I will be continuing to carry out close observations of activities, and conducting semi-structured 1:1 interviews with those that organise and have taken part in the activities. ResultsData collection so far comprises completed observations at the citizen juries (~96 hours), ongoing observations of the public panel meetings (~15 hours), and thirty semi-structured 1:1 interviews with public contributors and other stakeholders about their experiences of the activities they were involved in. Early data analysis indicates key themes of: jurors feeling heard, but unsure whether anybody was listening; stakeholders being impressed by informed jurors, but raising concerns over contributors becoming too ‘expert’; how who is at the table and what information is presented impacts what is discussed; differences between online and in-person participation; and public involvement not being a substitute for informing the public about how their data is used. Conclusion‘Who’ is involved, and ‘how’ PPIE activities are designed and run can facilitate or constrain discussion, enhancing or limiting public contributions. If public involvement is to achieve its aims, including increasing trustworthiness, deeper consideration of these factors by those who seek the public’s views in their data projects is recommended.
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公众参与大数据项目:一项民族志研究。
目标公众参与和参与(PIE)在大数据倡议和项目中发挥着越来越重要的作用。因此,更深入地了解所使用的不同方法非常重要。方法本研究使用民族志知情的定性案例研究来探索PIE。案例研究包括:三个公民陪审团,每个陪审团在八天内进行,要求陪审员考虑不同的现实世界健康数据举措;以及一个由区域数据库设立的公共小组,负责进行数据链接。数据收集正在进行中,我将继续对活动进行密切观察,并对组织和参与活动的人进行半结构化的1:1访谈。结果迄今为止的数据收集包括在公民陪审团完成的观察(~96小时),在公共小组会议上进行的观察(~15小时),以及对公共贡献者和其他利益相关者进行的30次半结构化1:1访谈,了解他们参与活动的经历。早期数据分析表明,关键主题包括:陪审员感觉被倾听,但不确定是否有人在听;利益相关者对知情的陪审员印象深刻,但对贡献者变得过于“专家”表示担忧;谈判桌上的人和提供的信息如何影响所讨论的内容;在线参与和亲自参与之间的差异;公众参与并不能代替告知公众他们的数据是如何使用的。结论“谁”参与,PPIE活动的“设计和运行方式”可以促进或限制讨论,增强或限制公众贡献。如果公众参与是为了实现其目标,包括提高可信度,建议那些在数据项目中征求公众意见的人更深入地考虑这些因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.50
自引率
0.00%
发文量
386
审稿时长
20 weeks
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