Abstract
Semantic knowledge graphs provide very significant benefits for structuring and analysing huge amounts of aggregated data across diverse heterogeneous sources. Beyond quick and efficient data query and analysis, they facilitate inference from data and generation of insights for several purposes. With the multi-faceted global challenges posed by the COVID-19 pandemic, this research focused on the use of a semantic knowledge graph to model, structure and store COVID-related news articles centrally and semantically towards knowledge discovery, knowledge acquisition and advanced data analytics for understanding varying metrics relating to the virus towards curbing its spread. The semantic knowledge graph provides a platform for researchers, data analysts and data scientists across societal sectors to investigate and recommend strategies towards addressing the challenges it poses to the global society.