Thoughts on Data Governance and the Impact of COVID-19

On February, 3, 2020, the Chinese government held a meeting to highlight the major challenge that COVID-19 would present to China's system of governance. They emphasized that without the support of good data, it would be impossible to respond quickly and allocate appropriate medical resources and take other appropriate measures to contain the epidemic.

With data governance, standard open APIs make data collection more efficient; unified data standards accelerate data convergence; cross-platform data extraction and tracing eliminate silos and facilitate openness and sharing; private data is more secure, and reliability is improved.

Multiple e-government mini-apps with in-app QR "health codes" are accelerating the informatization of the citizenry. With data governance and sharing, in the near future, we may see a single QR code for all applications. Regularizing the online epidemic emergency response system can reduce the daily administrative management costs, enable more data to flow, and create more value. People voluntarily declare their health information to obtain the health QR codes that reflect their health status, and they can then use these codes to gain access to public places such as housing communities, office buildings, or public transit. In the early stages of an epidemic, the use of QR codes enhances safety by removing the need to gather together when waiting in line to fill out various forms related to the epidemic. Government agencies also no longer need to arrange for large groups of people to gather in place for screening. As the epidemic is gradually brought under control, the QR code can be used for contact tracing, which makes it easier to get people back to work. As work resumes in many regions, the cross-regional travel has introduced new challenges to epidemic control. Currently, the priority of data governance is to unify data standards of government agencies at all levels and across different departments to share data such as confirmed cases, suspected cases, close contacts, and regional risk levels.