Building an Open Resources Repository for COVID-19 Research
Tao Hu, Weihe Wendy Guan, Xinyan Zhu, Yuanzheng Shao, Lingbo Liu, Jing Du, Hongqiang Liu, Huan Zhou, Jialei Wang, Bing She, Luyao Zhang, Zhibin Li, Peixiao Wang, Yicheng Tang, Ruizhi Hou, Yun Li, Dexuan Sha, Yifan Yang, Ben Lewis, Devika Kakkar, Shuming Bao
Abstract
The COVID-19 outbreak is a global pandemic declared by the World Health Organization, with rapidly increasing cases in most countries. A wide range of research is urgently needed for understanding the COVID-19 pandemic, such as transmissibility, geographic spreading, risk factors for infections, and economic impacts. Reliable data archive and sharing are essential to jump-start innovative research to combat COVID-19. This research is a collaborative and innovative effort in building such an archive, including the collection of various data resources relevant to COVID-19 research, such as daily cases, social media, population mobility, health facilities, climate, socioeconomic data, research articles, policy and regulation, and global news. Due to the heterogeneity between data sources, our effort also includes processing and integrating different datasets based on GIS (Geographic Information System) base maps to make them relatable and comparable. To keep the data files permanent, we published all open data to the Harvard Dataverse (https://dataverse.harvard.edu/dataverse/2019ncov), an online data management and sharing platform with a permanent Digital Object Identifier number for each dataset. Finally, preliminary studies are conducted based on the shared COVID-19 datasets and revealed different spatial transmission patterns among mainland China, Italy, and the United States.