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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">IJPDS</journal-id>
      <journal-title-group>
        <journal-title>International Journal of Population Data Science</journal-title>
        <abbrev-journal-title>IJPDS</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="epub">2399-4908</issn>
      <publisher>
        <publisher-name>Swansea University</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.23889/ijpds.v10i3.3181</article-id>
      <article-id pub-id-type="publisher-id">10:3:151</article-id>
      <title-group>
        <article-title>Novel network analysis of all research requests in Scotland</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Alrouh</surname>
            <given-names initials="B">Bachar</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Harwin</surname>
            <given-names initials="J">Judith</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Hargreaves</surname>
            <given-names initials="C">Claire</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Humphreys</surname>
            <given-names initials="L">Leslie</given-names>
          </name>
          <xref ref-type="aff" rid="affil-2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Barlow</surname>
            <given-names initials="C">Charlotte</given-names>
          </name>
          <xref ref-type="aff" rid="affil-2">2</xref>
        </contrib>
      </contrib-group>
      <aff id="affil-1"><label>1</label><institution>Lancaster University, Lancaster, United Kingdom</institution></aff>
      <aff id="affil-2"><label>2</label><institution>University of Central Lancashire, Preston,
        United Kingdom</institution></aff>
      <pub-date>
        <day>01</day>
        <month>06</month>
        <year>2025</year>
      </pub-date>
      <pub-date date-type="collection" publication-format="electronic">
        <year>2025</year>
      </pub-date>
      <volume>8</volume>
      <issue>4</issue>
      <elocation-id>3181</elocation-id>
      <permissions>
        <license license-type="open-access"
          xlink:href="https://creativecommons.org/licences/by/4.0/">
          <license-p>This work is licenced under a Creative Commons Attribution 4.0 International
            License.</license-p>
        </license>
      </permissions>
      <self-uri xlink:href="https://ijpds.org/article/view/3181">This article is available from the
        IJPDS website at: https://ijpds.org/article/view/3181</self-uri>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Objectives</title>
      <p>Research Data Scotland (RDS) launched the Researcher Access Service (RAS) in 2024. The
        service was codesigned to meet researcher and data controller needs and maximise the value
        of and scale administrative linked data in Scotland. Analysis was carried out on all
        research requests in Scotland since 2015 to identify datasets most commonly asked for in
        combination to scale the service efficiently.</p>
    </sec>
    <sec>
      <title>Methods</title>
      <p>A dataset that included all research requests in Scotland since 2015 was analysed to
        identify all unique datasets requested for research in Scotland. Network analysis was then
        used to understand the relationships and connections between datasets. The networks were
        visualised, and different parameters were used to better understand connections. Community
        detection was used to identify the datasets which needed to be provided together to maximise
        the number of projects which could use the Researcher Access Service pathway.</p>
    </sec>
    <sec>
      <title>Result</title>
      <p>The work identified that there have been 123 unique datasets requested for research in
        Scotland since 2015. Of these 123, 114 datasets were datasets not already available through
        the Researcher Access Service.</p>
      <p>The top five most requested datasets that were requested in combination with RAS datasets,
        alongside the number of times requested are as follows:</p>
      <list list-type="number">
        <list-item>
          <p>SBR (Scottish Birth Record) – 131</p>
        </list-item>
        <list-item>
          <p>SICSAG (Scottish Intensive Care Society Audit Group) – 84</p>
        </list-item>
        <list-item>
          <p>ECOSS (Electronic Communication of Surveillance in Scotland) – 75</p>
        </list-item>
        <list-item>
          <p>SCI Diabetes (Diabetes Register) – 70</p>
        </list-item>
        <list-item>
          <p>NRS Stillbirths – 64</p>
        </list-item>
      </list>
      <p>A number of communities of datasets were identified, for example Education datasets, health
        datasets, and imaging datasets. Identifying these communities of dataset requests, the need
        for groups of datasets to be provided together through the RAS became evident.</p>
    </sec>
    <sec>
      <title>Conclusion</title>
      <p>The work has informed decisions on how best to scale the service. Only when we consider the
        combinations of datasets being requested and the connections between datasets, are we able
        to design a modern, scalable and sustainable service.</p>
    </sec>
  </body>
</article>