Introduction

In December 2019, an acute respiratory disease that causes severe symptoms such as fever, pneumonia and cough has emerged in Wuhan, Mainland China. Caused by SARS-CoV-2 virus, this contagious disease (so-called COVID-19) has spread all over the world causing a pandemic with thousands of morbidities and mortalities. In early March 2020, the pandemic reached Tunisia. Due to the harmful characteristics of the disease, the Tunisian government has decided several measures to control the transmission and the status of the infection in the country including mobility restrictions and restructuration of health systems.

SPEED is created as a system for the epidemiological surveillance of COVID-19 pandemic in Tunisia. This project integrates various types of data related to 2020 coronavirus epidemic in Tunisia in Wikidata, a free knowledge base in RDF format available online at https://www.wikidata.org/, and utilize them later to generate valuable statistical knowledge about the situation of COVID-19 pandemic in Tunisia and worldwide that can be useful for health specialists, research scientists and leaders to support their decisions. The development of these clinical, scholarly, epidemiological and environmental information related to the contagious disease is based on the ontological reasoning of Wikidata using SPARQL, a query language for linked data.

Acknowledgement

We thank Wikimedia community and IEEE Tunisia for their support to the work and Fariz Darari from Faculty of Computer Science, Universitas Indonesia for creating a few SPARQL queries that were used in this project.

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