ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume VI-4/W2-2020
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., VI-4/W2-2020, 135–141, 2020
https://doi.org/10.5194/isprs-annals-VI-4-W2-2020-135-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., VI-4/W2-2020, 135–141, 2020
https://doi.org/10.5194/isprs-annals-VI-4-W2-2020-135-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  15 Sep 2020

15 Sep 2020

INTEGRATION OF HETEROGENEOUS CORONAVIRUS DISEASE COVID-19 DATA SOURCES USING OGC SENSORTHINGS API

T. Santhanavanich, C. Kim, and V. Coors T. Santhanavanich et al.
  • University of Applied Sciences Stuttgart, Schellingstraße 24, 70174 Stuttgart, Germany

Keywords: SensorThings, COVID-19, Smart Cities, Urban data, Open Geospatial Consortium

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.