Curating, Enriching and FAIRifying Datasets from the Brazilian COVID-19 Vaccination

Marcus Vinicius Ferreira Gonçalves, Jamile Santos, Caio Zava Ferreira, Jorge Juan Zavaleta Gavidia, Sérgio Manuel Serra da Cruz, Jonice Oliveira
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Abstract

As the world struggles to face the challenges of vaccination against COVID-19, more attention needs to be paid to the issues related to the lack of transparency and accessibility of curated vaccination datasets. Among the strategies to combat COVID-19, vaccination and data-centered epidemiological investigations are the best ones. This paper presents the process of building cured and annotated datasets with provenance metadata. The primary dataset is based on the registration data of the Vaccination Campaign against COVID-19 in Brazil. The dataset contains thousands of records processed up to March 2021. The data were analyzed, treated, cross-checked, and linked with other sources to correct and complement them, resulting in cured datasets and aligned to the FAIR Data principles.
管理、丰富和公平化巴西COVID-19疫苗接种数据集
在全世界努力应对COVID-19疫苗接种挑战的同时,需要更多地关注与精心策划的疫苗接种数据集缺乏透明度和可及性相关的问题。在抗击COVID-19的战略中,疫苗接种和以数据为中心的流行病学调查是最好的策略。本文介绍了用来源元数据构建修复和注释数据集的过程。主要数据集基于巴西COVID-19疫苗接种运动的登记数据。该数据集包含截至2021年3月处理的数千条记录。对数据进行了分析、处理、交叉检查,并与其他来源进行了联系,以纠正和补充这些数据,形成了完整的数据集,并符合FAIR数据原则。
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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