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.

翻译：新的COVID-19疾病(COVID-19,简称COVID-19)爆发SARS-COV-2大流行,要求赋予现有医疗、经济和社会紧急情况后端系统以数据分析能力,这些系统在利用数据分析方面的一个障碍是缺乏一个统一的框架或参考模型。本源被强调为弥合这一差距的一个有希望的解决办法,它正式代表COVID-19概念,如症状、感染率、接触跟踪和药物建模。基于本体学的解决办法使各种数据来源得以整合,从而更好地了解流行病数据,通过查明流行病热点和知识驱动的推断、推理和建议来管理明智的锁定,解决周围的问题。