A survey of epidemic management data models

被引:1
|
作者
Gao, Yongchao [1 ]
Wang, Qiuyue [1 ,4 ]
Fox, Mark S. [2 ]
Qian, Heng [3 ]
机构
[1] Qilu Univ Technol, Shandong Comp Sci Ctr, Jinan, Peoples R China
[2] Univ Toronto, Toronto, ON, Canada
[3] Qilu Univ Technol, Shandong Comp Sci Ctr, Jinan, Peoples R China
[4] Qilu Univ Technol, Shandong Comp Sci Ctr, 19, Keyuan Rd, Jinan 250014, Shandong, Peoples R China
关键词
COVID-19; data interoperability; epidemiology; epidemic management; ontology; ONTOLOGY; SURVEILLANCE; DESIGN;
D O I
10.1177/14604582231180226
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
The COVID-19 epidemic has demonstrated the important role that data plays in the response to and management of public health emergencies. It has also heightened awareness of the role that ontologies play in the design of semantically precise data models that improve data interoperability among stakeholders. This paper surveys vocabularies and ontologies relevant to the task of achieving epidemic-related data interoperability. The paper first reviews 16 vocabularies and ontologies with respect to the use cases. Next it identifies patterns of knowledge that are common across multiple vocabularies and ontologies, followed by an analysis of patterns that are missing, based on the use cases. Conclusions show that existing vocabularies and ontologies provide significant coverage of the concepts underlying epidemic use cases, but there remain gaps in the coverage. More work is required to cover missing but significant concepts.
引用
收藏
页数:20
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