Geospatial and Semantic Mapping Platform for Massive COVID-19 Scientific Publication Search

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Abstract
Thousands of results of scientific publications on the topic of COVID-19 have emerged within a short time, raising significant challenges for scholars to organize the research, or even synthesize the knowledge in a timely or comprehensive manner. To facilitate this, we have developed a geospatial and semantic mapping platform to search and organize these large and unmapped digital collections. The semantic map visualizes research topics based on customized natural language processing algorithms, which helps users to identify their content of specific interest beyond keyword searches in web search engines. The resultant geospatial map extracts all the location names mentioned in the publications, illustrating where COVID-19 studies have been conducted and where neglected study areas might exist. The system has been deployed as a web service for public access.

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