论文标题
CODO：用于收集和分析COVID-19数据的本体论
CODO: An Ontology for Collection and Analysis of Covid-19 Data
论文作者
论文摘要
病例和患者信息（CODO）的COVID-19本体论提供了一个模型，用于收集和分析有关COVID-19的大流行的数据。本体论提供了基于标准的开源模型，可促进来自异质数据源的数据集成。本体论是通过分析数据集，文献，服务等不同的COVID-19数据来源设计的。本体论遵循词汇的最佳实践，通过重新使用其他领先词汇表的概念，并使用W3C标准标准RDF RDF，OWL，SWRL和SPARQL。本体论已经拥有一个独立的用户，并纳入了印度政府的现实世界数据。
The COviD-19 Ontology for cases and patient information (CODO) provides a model for the collection and analysis of data about the COVID-19 pandemic. The ontology provides a standards-based open-source model that facilitates the integration of data from heterogeneous data sources. The ontology was designed by analysing disparate COVID-19 data sources such as datasets, literature, services, etc. The ontology follows the best practices for vocabularies by re-using concepts from other leading vocabularies and by using the W3C standards RDF, OWL, SWRL, and SPARQL. The ontology already has one independent user and has incorporated real-world data from the government of India.
