A Study on Comparative Analysis of COVID-19 Datasets

Genc Hamzaj, Z. Dika, Isak Shabani
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引用次数: 1

Abstract

Abstract In December 2019 a virus named COVID-19 appeared in China, precisely in the city of Wuhan. This virus was declared a global pandemic by the World Health Organization in March 2020. Since no adequate medical treatment has yet been discovered for this virus, many world institutions are committed to share with each other the data they collect and process in their laboratories. A large amount of these data is shared with citizens in order to inform about the risk that threaten us by virus COVID-19. Various credible world institutions such as the World Health Organization (WHO), Johns Hopkins University (JHU), the European Centre for Disease Prevention and Control (ECDC), etc., are providing various statistical data to address the issues raised by this emergent situation, but these reports in some cases are putting doubts on the completeness and the transparency of the data, which are not sufficiently processed and which then create confusion about the risks that we are facing. In this paper we are conducting a study of the quality of current global datasets from the must credible sources related to COVID-19. Also, we are comparing datasets collected from Republic of Kosovo and Republic of North Macedonia with corresponding data from WHO, ECDC and JHU datasets. To analyze datasets from different sources, we are using Power BI tool, making the improvement through the implementation of adequate dimensions and methods of improving the quality of datasets.
COVID-19数据集对比分析研究
2019年12月,一种名为COVID-19的病毒出现在中国,正是在武汉市。世界卫生组织于2020年3月宣布该病毒为全球大流行。由于尚未发现针对这种病毒的适当治疗方法,许多世界机构承诺相互分享它们在实验室收集和处理的数据。与公民共享大量这些数据,以便了解COVID-19病毒威胁我们的风险。世界卫生组织(卫生组织)、约翰·霍普金斯大学(约翰·霍普金斯大学)、欧洲疾病预防和控制中心等各种可靠的世界机构正在提供各种统计数据,以解决这一紧急情况所引起的问题,但这些报告在某些情况下对数据的完整性和透明度提出了质疑,这些数据没有得到充分处理,从而使我们对所面临的风险产生混淆。在本文中,我们正在对来自与COVID-19相关的最可靠来源的当前全球数据集的质量进行研究。此外,我们正在将从科索沃共和国和北马其顿共和国收集的数据集与世卫组织、ECDC和JHU数据集的相应数据集进行比较。为了分析来自不同来源的数据集,我们使用Power BI工具,通过实施适当的维度和方法来提高数据集的质量,从而进行改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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