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

Xinyue Ye, Jiaxin Du, Xi Gong, Saiyang Na, Weimin Li, Sonali Kudva

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Article number5
JournalJournal of Geovisualization and Spatial Analysis
Volume5
Issue number1
DOIs
StatePublished - Jun 2021
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Computers in Earth Sciences
  • Earth and Planetary Sciences (miscellaneous)
  • Geography, Planning and Development

Keywords

  • COVID-19
  • Geospatial map
  • Knowledge discovery
  • Semantic map

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