Public perceptions of good data management: Findings from a UK-based survey

Abstract

Low levels of public trust in data practices have led to growing calls for changes to data-driven systems, and in the EU, the General Data Protection Regulation provides a legal motivation for such changes. Data management is a vital component of data-driven systems, but what constitutes ‘good’ data management is not straightforward. Academic attention is turning to the question of what ‘good data’ might look like more generally, but public views are absent from these debates. This paper addresses this gap, reporting on a survey of the public on their views of data management approaches, undertaken by the authors and administered in the UK, where departure from the EU makes future data legislation uncertain. The survey found that respondents dislike the current approach in which commercial organizations control their personal data and prefer approaches that give them control over their data, that include oversight from regulatory bodies or that enable them to opt out of data gathering. Variations of data trusts – that is, structures that provide independent stewardship of data – were also preferable to the current approach, but not as widely preferred as control, oversight and opt out options. These features therefore constitute ‘good data management’ for survey respondents. These findings align only in part with principles of good data identified by policy experts and researchers. Our findings nuance understandings of good data as a concept and of good data management as a practice and point to where further research and policy action are needed.

Data intermediary

“…• data trusts, in which the intermediary will take on responsibility to steward supplier data for agreed purposes. Data trusts may be based on fiduciary duties to act in the suppliers' interests (Edwards, 2004;Hall & Pesenti, 2017;O'Hara, 2019;Delacroix & Lawrence, 2019; GPAI/Aapti/ODI 2021), and/or be based on a contractual or statutory legal obligations (ODI, 2018;Reed et al, 2019;Ada Lovelace, 2021; GPAI/Aapti/ODI 2021); • data commons, with members voluntarily 'pooling' their data for the benefit of a specific community (Wong & Henderson, 2020;Hartman et al 2020), or for the general public interest Data Governance Act; • data cooperatives, often referring to a data intermediary owned and democratically controlled by its members who delegate control over data about them (Hartman et al, 2020); • data collaboratives, where participants from different sectors -including private companies, research institutions, and government agencies -can exchange data and data expertise to help solve public problems (S.…”

The revolution that did not happen: Telematics and car insurance in the 2010s

“…The use of telematics devices implies monitoring and recording customers' behaviour. It has been shown that consumers are less likely to consent to share their data when it is accessible to companies (Hartman et al, 2020). While access to driving data has been less hotly debated than health data (Cheung, 2020), the revolution promised by Big Data may also be hindered by customer reluctance.…”

Mediatisation and datafication in the global COVID-19 pandemic: on the urgency of data literacy

“…That is not to say that citizens have no clear expectations towards datafication. To the contrary, recent findings imply that users want more control and accountability ( Hartman et al, 2020 ); but experts need to listen closer to these demands and engage in dialogues with the public about perceived risks.…”