by Andrew J. Zahuranec, Aditi Ramesh, Andrew Young, Stefaan Verhulst, and Brennan Lake
Thinking about March 2020 can be a surreal experience. This time last year, people around the world were just entering lockdown — for what many assumed would be a few weeks. Restaurants and hotels shut their doors. Busy squares emptied out. People around the world dramatically altered their movements to avoid spreading the disease to their neighbors and loved ones. For some time, the impact of these changes remained unclear.
To understand the cumulative effects of these shocks on disease spread, researchers and policymakers scrambled to find new ways to understand the impact of these changes on disease spread and public well-being. One approach that emerged centered on the analysis of mobility data, data about the location of a device passively produced through normal activity.
Two weeks ago, the Open Data Institute published a new report from The GovLab and Cuebiq studying this approach, The Use of Mobility Data for Responding to the COVID-19 Pandemic. Extracted from an analysis of 51 uses of mobility data around the world, the report details what mobility data is, the ethical considerations that must be made before it can be used, and lessons it provides for pandemic response. The report’s findings are supplemented by five case studies that look specifically at applications in Canada, the European Union, Chile, United Kingdom, and various other countries. Each of these case studies rely on several interviews with project participants to understand what they accomplished, difficulties they encountered, and lessons they learned from their experiences. Each piece was subject to a peer review process to identify gaps and improve the analysis’s overall quality.
In line with The GovLab’s other work, all the projects identified are data collaboratives, a new form of collaboration, beyond the public-private partnership model, in which participants from different sectors — in particular companies — exchange their data to create public value. The analysis seeks to identify if mobility data can be used responsibly and in a way consistent with local expectations.
Synthesis Report and Case Studies
These documents fill real gaps in the public’s understanding of mobility data. To make sense of how businesses, governments, and news organizations alike have used this resource, the synthesis report begins first with an overview of the various data sources from which mobility data can be derived and the formats it can be presented in. It describes complex terminology like call detail records, data generated each time a mobile phone connects to a network by sending or receiving a voice call or text message, and SDK smartphone-derived GPS, data transmitted about a device’s geographic location from a smartphone’s built-in sensor. It then explains the implications that this data has on individual privacy and what organizations can do to protect individuals from harm. These explanations are essential given that mobility data can be highly sensitive.
Following these explanations, the synthesis report and case studies then provide insights that the researchers learned through desk research on the data collaboratives and subsequent interviews. The documents note, for instance, the need for mobility data projects to have real-time, locally relevant data, intermediaries who can connect those who can supply data with those who can use it, and regulatory clarity. Project participants commonly faced obstacles from a lack of interoperability, shifting project focus, inherent limitations in the data, a lack of resources, and a fear of how they would be perceived. Given these facts, the documents note that other organizations might want to define project scope, identify trusted intermediaries, support attempts to develop international standards around responsible data use, and create data stewards who can coordinate data re-use. Each of these insights is identified in the synthesis report and explained in more detail in relevant case studies.
Findings and Recommendations
Based on this work, the report then offers nine recommendations for how organizations might pursue more effective, sustainable, and responsible re-use of mobility data through data collaboration. Understanding the complexities around each application, it nonetheless suggests:
- Developing and clarifying governance framework to enable the trusted, transparent, and accountable reuse of privately held data in the public interest under a clear regulatory framework
- Building capacity of organizations in the public and private sector to reuse and act on data through investments in training, education, and reskilling of relevant authorities; especially driving support for institutions in the Global South
- Establishing data stewards in organizations who can coordinate and collaborate with counterparts on using data in the public’s interest and acting on it.
- Establishing dedicated and sustainable Corporate Social Responsibility programs in organisations to coordinate and collaborate with counterparts on using and acting upon data in the public’s interest.
- Building a network of data stewards to coordinate and streamline efforts while promoting greater transparency; as well as exchange best practices and lessons learned.
- Engaging the public about how their data is being used so they can clearly articulate how they want their data to be responsibly used, shared, and protected.
- Promoting technological innovation through collaboration between funders (e.g. governments and foundations) and researchers (e,g. data scientists) to develop and deploy useful, privacy-preserving technologies.
- Unlocking funds from a variety of sources to ensure projects are sustainable and can operate long term.
- Focusing on evidence gathering by publishing easily accessible research and creating dedicated centres to develop best practices.
The repository, which informed some of the analysis, includes over 50 examples of data collaboratives involving mobility data. Through the site, individuals can view how different data types have been used, the privacy and security measures taken, and the geographic distribution of projects. While neither comprehensive nor representative, the highlighted examples raise questions about what is involved in responsible and ethical mobility data re-use.
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