RESEARCH & POLICY ANALYSIS
Policy Brief: Strengthening Data Governance for Effective Use of Open Data and Big Data Analytics for Combating COVID-19
December 29, 2020
The fast spread and pervasive impact of COVID-19 require governments to provide effective, timely, and inclusive responses to manage the pandemic. In addition to traditional data sources and data analytics tools, governments rely on open data and big data analytics in responding to COVID-19. Open data and big data analytics are required for i) conducting real-time situation analysis, contact tracing, and early and timely diagnosis for effective containment; ii) facilitating coordination and collaboration between national and local governments and fostering the ownership and accountability of local governments; iii) securing public trust in government through better transparency and improved communications; iv) countering misinformation; v) identifying and addressing special vulnerabilities and needs of vulnerable groups by gathering disaggregated data; and vi) supporting effective management of medical equipment supplies and demands.
“Open data” are data which are made accessible and available in a standardized machine-readable format and under a license that allows it to be re-used and re-shared. Because the type, format and quality of data vary significantly, it is a challenge to certify the data and put them in effective use with value added. “Big data” are usually associated with high velocity, volume and variety and often defined within political and social contexts as “a cluster or assemblage of data-related ideas, resources, and practices”. Big data are also referred to as an “imprecise description of a rich and complicated set of characteristics, practices, techniques, ethical issues and outcomes all associated with data”. There are many open and big data sources such as open government data, citizen science, and crowdsourcing that provide updated information. Big data analytics can be used for deeper and more complex tasks such as the analysis of social media sentiment. Particularly, citizen science, which refers to the involvement of non-scientist citizens in the generation of new scientific knowledge, could effectively contribute to building resilient communities.
With a more prominent role of open data and big data analytics in addressing challenges of COVID-19, there have been increasing concerns about data privacy and security, which also put in jeopardy public trust in data collection, use, and dissemination by government and relevant non-government stakeholders such as the private sector. According to a recent survey by IBM Policy Lab, almost half (49%) of the respondents across the US and the EU are more concerned about privacy as a result of contact tracing during the COVID-19 pandemic. This has become more complex due to the increase in data partnerships between government institutions and the private sector such as telecommunications and credit card companies for purposes of contact tracing and social distancing. The general public has expressed concerns about the unauthorized access and misuse of personal data as such access is often conducted without consent. The public is not duly informed about the legal or technical protocols governing such data partnerships between government institutions and the private sector. Such increasing public concerns about data privacy and security with regard to the use of open data and big data analytics for addressing COVID-19, which is often linked with data partnerships between government institutions and the private sector, have led to calls for strengthening data governance.
This Policy Brief communicates three key messages:
1. Instituting a robust data governance constitutes the foundation for effective use of open data and big data analytics for combatting COVID-19.
2. Data governance requires a holistic and whole-of-government approach with the engagement of all stakeholders and partners across sectors.
3. Data disaggregation is key during a pandemic, and it is imperative to enhance the capacity for the collection of disaggregated data to ensure the inclusion of vulnerable groups that are hit most.
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