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When biomedical crises strike, structural biologists worldwide respond by determining the structures of relevant proteins and their complexes, resulting in an avalanche of data that can be overwhelming without a resource designed to classify, annotate and validate them. An advanced information system is necessary to extract and infer knowledge from a deluge of uncurated and disjointed data and publications., As part of the global mobilization to combat the present pandemic, almost 100 000 COVID-19-related papers have been published and nearly a thousand models of macromolecules encoded by SARS-CoV-2 have been deposited in the Protein Data Bank within less than a year. The avalanche of new structural data has given rise to multiple resources dedicated to assessing the correctness and quality of structural data and models. Here, an approach to evaluate the massive amounts of such data using the resource https://covid19.bioreproducibility.org is described, which offers a template that could be used in large-scale initiatives undertaken in response to future biomedical crises. Broader use of the described methodology could considerably curtail information noise and significantly improve the reproducibility of biomedical research.