B. Dutta, P. Das, S. Mitra
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{"title":"A survey and classification of publicly available COVID-19 datasets","authors":"B. Dutta, P. Das, S. Mitra","doi":"10.56042/alis.v69i3.58950","DOIUrl":null,"url":null,"abstract":"The current study curates a list of authentic and open-access sources of alphanumeric COVID-19 pandemic data. We have gathered 74 datasets from 42 sources, including sources from 18 countries. The datasets are searched through the Kaggle and GitHub repositories besides Google, providing a representation of varieties of pandemic-related datasets. The datasets are categorized according to their sources-primary and secondary, and according to their geographical distribution. While analyzing the dataset, we came across some classes in which the datasets can be categorized. We present the categorization in the form of taxonomy and highlight the present COVID-19 data collection and use challenges. The study will help researchers and data curators in the identification and classification of pandemic data. © 2022, National Institute of Science Communication and Policy Research. All rights reserved.","PeriodicalId":42973,"journal":{"name":"Annals of Library and Information Studies","volume":null,"pages":null},"PeriodicalIF":0.4000,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Library and Information Studies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.56042/alis.v69i3.58950","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
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新冠肺炎公开数据集的调查和分类
当前的研究策划了一份字母数字新冠肺炎大流行数据的真实和开放获取来源列表。我们收集了来自42个来源的74个数据集,其中包括来自18个国家的来源。除了谷歌,这些数据集还通过Kaggle和GitHub存储库进行搜索,提供了各种与疫情相关的数据集的表示。数据集根据其主要来源和次要来源以及地理分布进行分类。在分析数据集时,我们发现了一些可以对数据集进行分类的类。我们以分类法的形式介绍了分类,并强调了当前新冠肺炎数据收集和使用方面的挑战。这项研究将帮助研究人员和数据管理员识别和分类疫情数据。©2022,美国国家科学传播与政策研究所。保留所有权利。
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