Peter Rose
University of California-San Diego
COVID-19-Net Knowledge Graph
ArcGIS Population-at-Risk dashboard for San Diego
Collection of online applications to explore COVID-19 risk factors
The COVID-19 knowledge graph is expected to support cross-disciplinary queries, e.g. about differences in outbreak characteristics across locations with different socio-demographic or environmental conditions, population health effects of viral strains, or patterns of imported vs community infection spread. Jupyter notebooks developed by the project are expected to be used by the research community to populate and query the knowledge graph.
- Data or model providers: We are interested in integrating publicly available datasets or models relevant to COVID-19 that complement our current Knowledge Graph and GIS Dashboards to provide an integrated NSF resource for COVID-19.
- Data or model users: Collaborate on use cases, data representation and standards, APIs, dashboards, etc.
- Knowledge Graph Developers: Explore federated queries across Knowledge Graphs.
- We are open for collaboration with NSF COVID projects, governments, and commercial companies, on issues related to COVID-19 knowledge graph construction and knowledge graph federation, as well as, more broadly, on cross-disciplinary data-intensive research problems at the intersection of biomedical and environmental sciences.
knowledge graphs dashboards GIS host pathogen strains mutations genetic epidemiology social characteristics economic characteristics housing characteristics demographic characteristics business characteristics employment populations at risk comorbidities