COVID-ARC is a data archive for multimodal (i.e., demographic information, clinical outcome reports, imaging scans) and longitudinal data related to COVID-19 and provide various statistical and analytic tools for researchers. There is an immediate need to study COVID-19, and this archive provides access to data along with user-friendly tools for researchers to perform analyses to better understand COVID-19 and encourage collaboration on this research. The COVID-19 pandemic is spreading rapidly across the world, and governments are imposing travel bans, quarantine laws, business and school closings, and many other restrictions in efforts to contain the virus and limit the spread. However, much is still unknown about COVID-19. There is an urgent need for scientists around the world to work together to model the virus, study how the virus has changed and will change over time, understand how it spreads, and discover a vaccine. The work from this project can also prepare scientists for future pandemics by putting the infrastructure in place to enable researchers to aggregate data and perform analyses quickly in the event of an emergency.
The approach is to develop a platform of networked and centralized web-accessible data archives to store multimodal data related to COVID-19 and make them broadly available and accessible to the world-wide scientific community to expedite research in this area due to the urgent nature of the COVID-19 pandemic. By leveraging previous work in developing data repositories and archival capabilities at the Laboratory of Neuro Imaging at the University of Southern California, COVID-ARC (COVID-19 Data Archive) aims to provide an efficient and secure data repository platform that facilitates data access and analysis. COVID-ARC provides tools for researchers to visualize and analyze various types of data as well as a website with tools for training, announcements, virtual information sessions, and a knowledgebase wherein researchers post questions and receive answers from the community.