INTEGRATION OF HETEROGENEOUS CORONAVIRUS DISEASE COVID-19 DATA SOURCES USING OGC SENSORTHINGS API
ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences
; VI-4/W2-2020:135-141, 2020.
Article
in English
| ProQuest Central | ID: covidwho-830987
ABSTRACT
The latest coronavirus (namely severe acute respiratory syndrome coronavirus 2 or COVID-19) was first detected in Wuhan, China, and spread throughout the world since December 2019. To tackle this pandemic, we need a tool to trace and predict trends of COVID-19 at global, national, and regional levels rapidly. Several organizations around the world offer access to COVID-19 related data. However, these data sources are heterogeneous in terms of data formats and protocols as different organizations developed them. To address this issue, a standard way to handle these datasets is needed. In this paper, we propose using the OGC SensorThings API to manage the COVID-19 dataset in a standard form and provide access to the general public. As a proof-of-concept, we implemented a COVID-19 data management platform based on the OGC SensorThings standard named COVID-19 SensorThings or in short COVID-STA. For a use case, we developed a real-time interactive web-based dashboard illustrating the COVID-19 dataset based on the COVID-STA. As a result, we proved that the OGC SensorThings API is suitable to use as a general standard for integrating the heterogeneous COVID-19 data.
Full text:
Available
Collection:
Databases of international organizations
Database:
ProQuest Central
Language:
English
Journal:
ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences
Year:
2020
Document Type:
Article
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