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<!DOCTYPE ArticleSet PUBLIC "-//NLM//DTD PubMed 2.0//EN" "http://www.ncbi.nlm.nih.gov:80/entrez/query/static/PubMed.dtd"[]>
<ArticleSet>
  <Article>
    <Journal>
      <PublisherName>Science and Education Publishing</PublisherName>
      <JournalTitle>Digital Technologies</JournalTitle>
      <Volume>1</Volume>
      <Issue>1</Issue>
      <PubDate PubStatus="epublish">
        <Year>2015</Year>
        <Month>07</Month>
        <Day>20</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>Big Data and Visualization: Methods, Challenges and Technology Progress</ArticleTitle>
    <FirstPage>33</FirstPage>
    <LastPage>38</LastPage>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName>Lidong</FirstName>
        <LastName>Wang</LastName>
        <Affiliation>Department of Engineering Technology, Mississippi Valley State University, USA</Affiliation>
      </Author>
      <Author>
        <FirstName>Guanghui</FirstName>
        <LastName>Wang</LastName>
      </Author>
      <Author>
        <FirstName>Cheryl Ann</FirstName>
        <LastName>Alexander</LastName>
      </Author>
    </AuthorList>
    <ArticleIdList>
      <ArticleId IdType="pii">DT2015117</ArticleId>
      <ArticleId IdType="doi">10.12691/dt-1-1-7</ArticleId>
    </ArticleIdList>
    <History>
      <PubDate PubStatus="received">
        <Year>2015</Year>
        <Month>06</Month>
        <Day>27</Day>
      </PubDate>
      <PubDate PubStatus="revised">
        <Year>2015</Year>
        <Month>07</Month>
        <Day>16</Day>
      </PubDate>
      <PubDate PubStatus="accepted">
        <Year>2015</Year>
        <Month>07</Month>
        <Day>20</Day>
      </PubDate>
    </History>
    <Abstract>Big Data analytics plays a key role through reducing the data size and complexity in Big Data applications. Visualization is an important approach to helping Big Data get a complete view of data and discover data values. Big Data analytics and visualization should be integrated seamlessly so that they work best in Big Data applications. Conventional data visualization methods as well as the extension of some conventional methods to Big Data applications are introduced in this paper. The challenges of Big Data visualization are discussed. New methods, applications, and technology progress of Big Data visualization are presented.</Abstract>
  </Article>
</ArticleSet>