Guiding principles to maintain public trust in the use of mobile operator data for policy purposes. (1st October 2021)
- Record Type:
- Journal Article
- Title:
- Guiding principles to maintain public trust in the use of mobile operator data for policy purposes. (1st October 2021)
- Main Title:
- Guiding principles to maintain public trust in the use of mobile operator data for policy purposes
- Authors:
- Jansen, Ronald
Kovacs, Karoly
Esko, Siim
Saluveer, Erki
Sõstra, Kaja
Bengtsson, Linus
Li, Tracey
Adewole, Wole A.
Nester, Jade
Arai, Ayumi
Magpantay, Esperanza - Abstract:
- Abstract: The COVID-19 pandemic has accelerated the use of mobile operator data to support public policy, although without a universal governance framework for its application. This article describes five principles to guide and assist statistical agencies, mobile network operators and intermediary service providers, who are actively working on projects using mobile operator data to support governments in monitoring the effectiveness of its COVID-19 related interventions. These are principles of necessity and proportionality, of professional independence, of privacy protection, of commitment to quality, and of international comparability. Compliance with each of these principles can help maintain public trust in the handling of these sensitive data and their results, and therefore keep citizen support for government policies. Three projects (in Estonia, Ghana, and the Gambia) were described and reviewed with respect to the compliance and applicability of the five principles. Most attention was placed on privacy protection, somewhat at the expense of the quality of the compiled indicators. The necessity and proportionality in the choice of mobile operator data can be very well justified given the need for timely, frequent and granular indicators. Explicitly addressing the five principles in the preparation of a project should give confidence to the statistical agency and its partners, that enough care has been exercised in the set up and implementation of the project, andAbstract: The COVID-19 pandemic has accelerated the use of mobile operator data to support public policy, although without a universal governance framework for its application. This article describes five principles to guide and assist statistical agencies, mobile network operators and intermediary service providers, who are actively working on projects using mobile operator data to support governments in monitoring the effectiveness of its COVID-19 related interventions. These are principles of necessity and proportionality, of professional independence, of privacy protection, of commitment to quality, and of international comparability. Compliance with each of these principles can help maintain public trust in the handling of these sensitive data and their results, and therefore keep citizen support for government policies. Three projects (in Estonia, Ghana, and the Gambia) were described and reviewed with respect to the compliance and applicability of the five principles. Most attention was placed on privacy protection, somewhat at the expense of the quality of the compiled indicators. The necessity and proportionality in the choice of mobile operator data can be very well justified given the need for timely, frequent and granular indicators. Explicitly addressing the five principles in the preparation of a project should give confidence to the statistical agency and its partners, that enough care has been exercised in the set up and implementation of the project, and should convey trust to public and government in the use mobile operator data for policy purposes. … (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:
- 2021-10-01
- Subjects:
- COVID-19 response -- Fundamental Principles of Official Statistics -- mobile operator data -- privacy protection -- 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.2021.21 ↗
- 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:
- 18983.xml