A survey of epidemic management data models

Author:

Gao Yongchao1,Wang Qiuyue2ORCID,Fox Mark S3,Qian Heng4

Affiliation:

1. Shandong Computer Science Center, Qilu University of Technology, Jinan, China

2. Shandong Computer Science Center, Qilu University of Technology,Jinan, China

3. University of Toronto, Toronto, ON, Canada

4. Qilu University of Technology, Shandong Computer Science Center, Jinan, China

Abstract

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.

Funder

Ministry of Science and Technology of the People’s Republic of China

Department of Science and Technology of Shandong Province

Publisher

SAGE Publications

Subject

Health Informatics

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