With approximately 2.5 million new scientific publications per year and an annual growth rate of 8-9%, researchers are increasingly faced with the task of maintaining an overview of the publication relevant publications for them. Since the publications are available as pseudo-digitized PDF files and are therefore collections of unstructured texts and illustrations, the possibilities of machines to support science in literature research is unfortunately very limited. This is what the Open Research Knowledge Graph (ORKG – https://www.orkg.org) wants to change. The ORKG aims at describing scientific publications in a structured way and to deposit them in a knowledge graph in order to make its content machine-actionable and FAIR (Findable, Accessible, Interoperable and Reusable) and thus easier to find and compare. In this project, content from selected publications in the field of virology will be systematically added to the ORKG. The focus will be on publications on the influence of mutations on pandemic events of SARS-CoV-2 and other zoonotic viruses. In addition, the suitability of the ORKG as an infrastructure for the creation of subject-specific knowledge graphs will be evaluated exemplarily for virology.