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<article article-type="research-article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="aggregator">72010604</journal-id>
      <journal-title>Electronic Imaging</journal-title>
      <issn pub-type="ppub">2470-1173</issn><issn pub-type="epub"></issn>
      <publisher>
        <publisher-name>Society for Imaging Science and Technology</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.2352/ISSN.2470-1173.2017.5.SDA-105</article-id>
      <article-id pub-id-type="sici">2470-1173(20170129)2017:5L.173;1-</article-id>
      <article-id pub-id-type="publisher-id">s24.phd</article-id>
      <article-id pub-id-type="other">/ist/ei/2017/00002017/00000005/art00024</article-id>
      <article-categories>
        <subj-group>
          <subject>Articles</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Designing a Cloud-based 3D Visualization Engine for Smart Cities</article-title>
      </title-group>
      <contrib-group>
        <contrib>
          <name>
            <surname>Holliman</surname>
            <given-names>Nicolas</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Turner</surname>
            <given-names>Mark</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Dowsland</surname>
            <given-names>Stephen</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Cloete</surname>
            <given-names>Richard</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Picton</surname>
            <given-names>Thomas</given-names>
          </name>
        </contrib>
      </contrib-group>
      <pub-date>
        <day>29</day>
        <month>01</month>
        <year>2017</year>
      </pub-date>
      <volume>2017</volume>
      <issue>5</issue>
      <fpage>173</fpage>
      <lpage>178</lpage>
      <permissions>
        <copyright-year>2017</copyright-year>
      </permissions>
      <abstract>
        <p>Urban data is being collected in increasing quantities as smart cities around the globe seek to understand and improve their operations and plan their growth. This trend is set to continue as UNICEF predicts that 75% of people will live in cities by the end of the 21st century. One
 of the aims of Smart City initiatives is to improve inclusivity by communicating more about the city to citizens and organizational stakeholders. The large amounts of data and computational cost of the calculations required to do this mean that cloud-based analytics and visualization is an
 attractive option as it can deliver results to virtually any client device. In this article, we describe the design and implementation of the Urban Insight Cloud Engine (UICE) a pilot cloud-based 3D visualization system for Smart Cities that has been created using open software and data
 sets. This delivers a continuous live view of data collected by Urban Observatory sensors in the city of Newcastle-upon-Tyne, UK. We precede this with a discussion of our experience designing the facilities that exist, are being built, or are being planned to be built, to support our visualization
 research and production at Newcastle University.</p>
      </abstract>
      <kwd-group>
        <kwd>STEREOSCOPIC VISUALIZATION</kwd>
        <kwd>SMART CITY</kwd>
        <kwd>IOT</kwd>
        <kwd>BIG DATA</kwd>
        <kwd>STEREOSCOPIC DISPLAYS</kwd>
        <kwd>CLOUD COMPUTING</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
