A unique commonality among the diverse Projects and Cores of this Center is the need for rigorous and reproducible data. While the successful discovery of novel antivirals is inherently multidisciplinary, data must be generated, collected, annotated, and acted upon at each step of the process by biologists and chemists from target validation to late-stage lead optimization. The goal of this Core is to create a next-generation data infrastructure that allows for the efficient undertaking of these data tasks, as well as the dissemination of opendata to the larger scientific community. Innovative software will build on initial architecture developed for the open-science COVID Moonshot initiative for rapid antiviral discovery, which led to novel inhibitors of the SARSCoV- 2 Main Protease, while also supporting hundreds of projects across the globe through open-data practices. Early end-to-end collection of data and tracking of drug discovery project progression, will enable accelerated internal development, in addition to sources of data crucial for development of the global antiviral pipeline. All internal results, as well as compound logistics and prioritization, will be tracked and made available, thus providing the high quality data for machine learning models to augment rapid development, and for the computational community to build on. Data workflows and processes in addition to data and metadata ranging from target validation to preclinical development will ultimately be shared to the global community, spurring rapid global progress in antiviral discovery.