Does open data have the potential to improve the response of science to public health emergencies?

Open data was recognized as essential to prevent and treat pandemic infection through sharing, disseminating, and using relevant information. This study explores how and to what extent open data influenced the response of science to such emergencies from a quantitative perspective. Based on the genetic datasets for viruses associated with Ebola, SARS, MERS, and COVID-19, we analyze the efficiency of data sharing and dissemination from a knowledge flow perspective: "datasets→papers", "datasets→patents", and "datasets→papers→patents". The results showed: (1) From the early Ebola outbreak to the recent COVID-19 pandemic, data sharing has been increasingly open and timely. (2) Basic research and the developments of vaccine and medicine related to the pandemics have increasingly relied on open data, providing more data-driven alternatives. (3) From Ebola to COVID-19, the citation lags of highly cited datasets have decreased in both papers and patents, demonstrating that open data can accelerate the development of science and technology to address the epidemics. In conclusion, open data can potentially improve science's response to public health emergencies by saving precious time. Therefore, much greater efforts by the scientific community to open data are well deserved.