A Summary of Covid-19 Datasets

<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml"> <head> <title>A Summary of Covid-19 Datasets</title>  <meta charset="UTF-8"> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <meta http-equiv="X-UA-Compatible" content="ie=edge"> <meta name="title" content="A Summary of Covid-19 Datasets"> <meta name="description" content="This research presents a review of main datasets that are developed for COVID-19 research. We hope this collection will continue to bring together members of the computing community, biomedical experts, and policymakers in the pursuit of effective COVID-19 treatments and management policies. Many organizations, such as the World Health Organization (WHO), John Hopkins, National Institute of Health (NIH), COVID-19 open science table and such, in the world, have made numerous datasets available to the public. However, these datasets originate from a variety of different sources and initiatives. The purpose of this research is to summarize the open COVID-19 datasets to make them more accessible to the research community for health systems design and analysis. We also discuss the numerous resources introduced to support text mining applications throughout the COVID-19 literature; more precisely, we discuss the corpora, modelling resources, systems, and shared tasks introduced for COVID-19"/> <meta name="keywords" content="COVID-19, Text Mining, Public health, Risk, Public Health, COVID-19 Data, Data Science"/>   <meta name="dc.title" content="A Summary of Covid-19 Datasets"> <meta name="citation_author" content="Syed Raza Bashir "> <meta name="citation_author" content="Shaina Raza Vidhi Thakkar"> <meta name="citation_author" content="Vidhi Thakkar"> <meta name="citation_author" content=" Usman Naseem"> <meta name="dc.type" content="Article"> <meta name="dc.source" content="Computer Science & Information Technology (CS & IT), Vol.12, No.12"> <meta name="dc.date" content="2020-07-31"> <meta name="dc.identifier" content="10.5121/csit.2022.121219"> <meta name="dc.publisher" content="AIRCC Publishing Corporation"> <meta name="dc.rights" content="http://creativecommons.org/licenses/by/3.0/"> <meta name="dc.format" content="application/pdf"> <meta name="dc.language" content="en"> <meta name="dc.description" content="This research presents a review of main datasets that are developed for COVID-19 research. We hope this collection will continue to bring together members of the computing community, biomedical experts, and policymakers in the pursuit of effective COVID-19 treatments and management policies. Many organizations, such as the World Health Organization (WHO), John Hopkins, National Institute of Health (NIH), COVID-19 open science table and such, in the world, have made numerous datasets available to the public. However, these datasets originate from a variety of different sources and initiatives. The purpose of this research is to summarize the open COVID-19 datasets to make them more accessible to the research community for health systems design and analysis. We also discuss the numerous resources introduced to support text mining applications throughout the COVID-19 literature; more precisely, we discuss the corpora, modelling resources, systems, and shared tasks introduced for COVID-19."/>   <meta name="prism.publicationName" content="Computer Science & Information Technology (CS & IT)"> <meta name="prism.publicationDate" content="2020-07-31"> <meta name="prism.volume" content="12"> <meta name="prism.number" content="12"> <meta name="prism.section" content="Article"> <meta name="prism.startingPage" content="231">   <meta name="citation_journal_title" content=" Computer Science & Information Technology (CS & IT)"> <meta name="citation_publisher" content="AIRCC Publishing Corporation"> <meta name="citation_authors" content="Syed Raza Bashir, Shaina Raza, Vidhi Thakkar and Usman Naseem"> <meta name="citation_title" content="A Summary of Covid-19 Datasets "> <meta name="citation_online_date" content="2020-07-31"> <meta name="citation_volume" content="12"> <meta name="citation_issue" content="12"> <meta name="citation_firstpage" content="231"> <meta name="citation_author" content="Syed Raza Bashir "> <meta name="citation_author" content="Shaina Raza Vidhi Thakkar"> <meta name="citation_author" content="Vidhi Thakkar"> <meta name="citation_author" content=" Usman Naseem"> <meta name="citation_doi" content="10.5121/csit.2022.121219"> <meta name="citation_abstract_html_url" content="https://aircconline.com/csit/abstract/v12n12/csit121219.html"/> <meta name="citation_pdf_url" content="https://aircconline.com/csit/papers/vol12/csit121219.pdf"/>   <meta property="og:site_name" content="AIRCC" /> <meta property="og:type" content="article" /> <meta property="og:url" content="https://aircconline.com/csit/abstract/v12n12/csit121219.html"/> <meta property="og:title" content="A Summary of Covid-19 Datasets"> <meta property="og:description" content="This research presents a review of main datasets that are developed for COVID-19 research. We hope this collection will continue to bring together members of the computing community, biomedical experts, and policymakers in the pursuit of effective COVID-19 treatments and management policies. Many organizations, such as the World Health Organization (WHO), John Hopkins, National Institute of Health (NIH), COVID-19 open science table and such, in the world, have made numerous datasets available to the public. However, these datasets originate from a variety of different sources and initiatives. The purpose of this research is to summarize the open COVID-19 datasets to make them more accessible to the research community for health systems design and analysis. We also discuss the numerous resources introduced to support text mining applications throughout the COVID-19 literature; more precisely, we discuss the corpora, modelling resources, systems, and shared tasks introduced for COVID-19."/>   <meta name="google-site-verification" content="t8rHIcM8EfjIqfQzQ0IdYIiA9JxDD0uUZAitBCzsOIw" /> <meta name="yandex-verification" content="e3d2d5a32c7241f4" />  <link rel="icon" type="image/ico" href="../img/ico.ico"/> <link rel="stylesheet" type="text/css" href="../main1.css" media="screen" /> <style type="text/css"> a{ color:white; text-decoration:none; line-height:20px; } ul li a{ font-weight:bold; color:#000; list-style:none; text-decoration:none; size:10px;} .imagess { height:90px; text-align:left; margin:0px 5px 2px 8px; float:right; border:none; } #left p { font-family: CALIBRI; font-size: 16px; margin-left: 20px; font-weight: 500; } .right { margin-right: 20px; } #button{ float: left; font-size: 14px; margin-left: 10px; height: 28px; width: auto; background-color: #1e86c6; } </style> </head> <body> <div class="font"> <div id="wap"> <div id="page"> <div id="top"> <form action="https://airccj.org/csecfp/library/Search.php" method="get" target="_blank" > <table width="100%" cellspacing="0" cellpadding="0" > <tr class="search_input"> <td width="665" align="right"> </td> <td width="236" > <input name="title" type="text" value="Enter the paper title" class="search_textbox" onclick="if(this.value=='Enter the paper title'){this.value=''}" onblur="if(this.value==''){this.value='Enter the paper title'}" /> </td> <td width="59"> <input type="image" src="../img/go.gif" /> </td> </tr> <tr> <td colspan="3" valign="top"><img src="../img/top1.gif" alt="Academy & Industry Research Collaboration Center (AIRCC)" /></td> </tr> </table> </form> </div> <div id="font-face"> <div id="menu"> <a href="http://airccse.org">Home</a> <a href="http://airccse.org/journal.html">Journals</a> <a href="http://airccse.org/ethics.html">Ethics</a> <a href="http://airccse.org/conference.html">Conferences</a> <a href="http://airccse.org/past.html">Past Events</a> <a href="http://airccse.org/b.html">Submission</a> </div> <div id="content"> <div id="left"> <h2 class="lighter"><font size="2">Volume 12, Number 12, July 2022</font></h2> <h4 style="text-align:center;height:auto;"><a>A Summary of Covid-19 Datasets </a></h4> <h3>  Authors</h3> <p class="#left right" style="text-align:">Syed Raza Bashir<sup>1</sup>, Shaina Raza<sup>2</sup>, Vidhi Thakkar<sup>3</sup> and Usman Naseem<sup>4</sup>, <sup>1</sup>Toronto Metropolitan University, Canada, <sup>2</sup>University of Toronto, Canada, <sup>3</sup>University of Victoria, Canada, <sup>4</sup>Sydney International School of Technology and Commerce, Australia </p> <h3>  Abstract</h3> <p class="#left right" style="text-align:justify">This research presents a review of main datasets that are developed for COVID-19 research. We hope this collection will continue to bring together members of the computing community, biomedical experts, and policymakers in the pursuit of effective COVID-19 treatments and management policies. Many organizations, such as the World Health Organization (WHO), John Hopkins, National Institute of Health (NIH), COVID-19 open science table and such, in the world, have made numerous datasets available to the public. However, these datasets originate from a variety of different sources and initiatives. The purpose of this research is to summarize the open COVID-19 datasets to make them more accessible to the research community for health systems design and analysis. We also discuss the numerous resources introduced to support text mining applications throughout the COVID-19 literature; more precisely, we discuss the corpora, modelling resources, systems, and shared tasks introduced for COVID-19. </p> <h3>  Keywords</h3> <p class="#left right" style="text-align:justify">COVID-19, Text Mining, Public health, Risk, Public Health, COVID-19 Data, Data Science.</p><br> <button type="button" id="button"><a target="_blank" href="/csit/papers/vol12/csit121219.pdf">Full Text</a></button>   <button type="button" id="button"><a href="http://airccse.org/csit/V12N12.html">Volume 12, Number 12</a></button> <br><br><br><br><br> </div> <div id="right"> <div class="menu_right"> <ul> <li id="id"><a href="http://airccse.org/editorial.html">Editorial Board</a></li> <li><a href="http://airccse.org/arch.html">Archives</a></li> <li><a href="http://airccse.org/indexing.html">Indexing</a></li> <li><a href="http://airccse.org/faq.html" target="_blank">FAQ</a></li> </ul> </div> <div class="clear_left"></div> <br> </div> <div class="clear"></div> <div id="footer"> <table width="100%" > <tr> <td width="46%" class="F_menu"><a href="http://airccse.org/subscription.html">Subscription</a> <a href="http://airccse.org/membership.html">Membership</a> <a href="http://airccse.org/cscp.html">AIRCC CSCP</a> <a href="http://airccse.org/acontact.html">Contact Us</a> </td> <td width="54%" align="right"><a href="http://airccse.org/index.php"><img src="/csit/abstract/img/logo.gif" alt="" width="21" height="24" /></a><a href="http://www.facebook.com/AIRCCSE"><img src="/csit/abstract/img/facebook.jpeg" alt="" width="21" height="24" /></a><a href="https://twitter.com/AIRCCFP"><img src="/csit/abstract/img/twitter.jpeg" alt="" width="21" height="24" /></a><a href="http://cfptech.wordpress.com/"><img src="/csit/abstract/img/index1.jpeg" alt="" width="21" height="24" /></a></td> </tr> <tr><td height="25" colspan="2"> <p align="center">All Rights Reserved ® AIRCC</p> </td></tr> </table> </div> </div> </div> </div> </div> </div> </body> </html>

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A Summary of Covid-19 Datasets