Increasing resilience via the use of personal data: Lessons from COVID-19 dashboards on data governance for the public good. (12th November 2021)
- Record Type:
- Journal Article
- Title:
- Increasing resilience via the use of personal data: Lessons from COVID-19 dashboards on data governance for the public good. (12th November 2021)
- Main Title:
- Increasing resilience via the use of personal data: Lessons from COVID-19 dashboards on data governance for the public good
- Authors:
- Li, Veronica Qin Ting
Yarime, Masaru - Abstract:
- Abstract: Contemporary data tools such as online dashboards have been instrumental in monitoring the spread of the COVID-19 pandemic. These real-time interactive platforms allow citizens to understand the local, regional, and global spread of COVID-19 in a consolidated and intuitive manner. Despite this, little research has been conducted on how citizens respond to the data on the dashboards in terms of the pandemic and data governance issues such as privacy. In this paper, we seek to answer the research question: how can governments use data tools, such as dashboards, to balance the trade-offs between safeguarding public health and protecting data privacy during a public health crisis? This study used surveys and semi-structured interviews to understand the perspectives of the developers and users of COVID-19 dashboards in Hong Kong. A typology was also developed to assess how Hong Kong's dashboards navigated trade-offs between data disclosure and privacy at a time of crisis compared to dashboards in other jurisdictions. Results reveal that two key factors were present in the design and improvement of COVID-19 dashboards in Hong Kong: informed actions based on open COVID-19 case data, and significant public trust built on data transparency. Finally, this study argues that norms surrounding reporting on COVID-19 cases, as well as cases for future pandemics, should be co-constructed among citizens and governments so that policies founded on such norms can be acknowledged asAbstract: Contemporary data tools such as online dashboards have been instrumental in monitoring the spread of the COVID-19 pandemic. These real-time interactive platforms allow citizens to understand the local, regional, and global spread of COVID-19 in a consolidated and intuitive manner. Despite this, little research has been conducted on how citizens respond to the data on the dashboards in terms of the pandemic and data governance issues such as privacy. In this paper, we seek to answer the research question: how can governments use data tools, such as dashboards, to balance the trade-offs between safeguarding public health and protecting data privacy during a public health crisis? This study used surveys and semi-structured interviews to understand the perspectives of the developers and users of COVID-19 dashboards in Hong Kong. A typology was also developed to assess how Hong Kong's dashboards navigated trade-offs between data disclosure and privacy at a time of crisis compared to dashboards in other jurisdictions. Results reveal that two key factors were present in the design and improvement of COVID-19 dashboards in Hong Kong: informed actions based on open COVID-19 case data, and significant public trust built on data transparency. Finally, this study argues that norms surrounding reporting on COVID-19 cases, as well as cases for future pandemics, should be co-constructed among citizens and governments so that policies founded on such norms can be acknowledged as salient, credible, and legitimate. … (more)
- Is Part Of:
- Data & policy. Volume 3(2021)
- Journal:
- Data & policy
- Issue:
- Volume 3(2021)
- Issue Display:
- Volume 3, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 3
- Issue:
- 2021
- Issue Sort Value:
- 2021-0003-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-11-12
- Subjects:
- COVID-19 -- data governance -- data transparency -- data privacy -- public trust
Policy sciences -- Periodicals
Policy sciences -- Statistical methods -- Periodicals
Policy sciences -- Data processing -- Periodicals
Decision making -- Data processing -- Periodicals
320.60727 - Journal URLs:
- https://www.cambridge.org/core/journals/data-and-policy ↗
- DOI:
- 10.1017/dap.2021.27 ↗
- Languages:
- English
- ISSNs:
- 2632-3249
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 19734.xml