An Overview of Ontologies and Tool Support for COVID-19 Analytics
Not on the map. Why?
Abstract (arXiv)
The outbreak of the SARS-CoV-2 pandemic of the new COVID-19 disease (COVID-19 for short) demands empowering existing medical, economic, and social emergency backend systems with data analytics capabilities. An impediment in taking advantages of data analytics in these systems is the lack of a unified framework or reference model. Ontologies are highlighted as a promising solution to bridge this gap by providing a formal representation of COVID-19 concepts such as symptoms, infections rate, contact tracing, and drug modelling. Ontology-based solutions enable the integration of diverse data sources that leads to a better understanding of pandemic data, management of smart lockdowns by identifying pandemic hotspots, and knowledge-driven inference, reasoning, and recommendations to tackle surrounding issues.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 4 of its 37 references that are in the map. First posted on arXiv 12 Oct 2021.
Builds on
4 of 37 references.
References · 4
- 2020CODO: An Ontology for Collection and Analysis of Covid-19 Datacited by 11
- 2020A Survey of COVID-19 Contact Tracing Appscited by 8
- 2020An Interactive Data Visualization and Analytics Tool to Evaluate Mobility and Sociability Trends During COVID-19cited by 3
- 2020Towards Integrated and Open COVID-19 Datacited by 1
Built on by
Citing papers per year: 2022: 1.
1 paper.