<?xml version="1.0"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN" "JATS-journalpublishing1.dtd" [
]>
<article xml:lang="en" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML"
  dtd-version="1.2" article-type="abstract">
  <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.v10i3.3197</article-id>
      <article-id pub-id-type="publisher-id">10:3:165</article-id>
      <title-group>
        <article-title>Enabling Federated Access to Administrative Data and Beyond</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Lockhart-Jones</surname>
            <given-names initials="H">Hazel</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Biddle</surname>
            <given-names initials="J">Justin</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Lee</surname>
            <given-names initials="A">Alex</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Vau</surname>
            <given-names initials="J">John</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Bale</surname>
            <given-names initials="M">Michael</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Thompson</surname>
            <given-names initials="S">Simon</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
      </contrib-group>
      <aff id="affil-1"><label>1</label><institution>SeRP Swansea University, Swansea, 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>3197</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/3197">This article is available from the
        IJPDS website at: https://ijpds.org/article/view/3197</self-uri>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Objectives</title>
      <p>Enable federated access to datasets across multiple Trusted Research Environments (TREs)
        while adhering to the Five Safes framework and international standards. This approach
        enhances global interoperability, prioritizing flexibility, accessibility, and transparency
        to advance secure, collaborative research.</p>
    </sec>
    <sec>
      <title>Method</title>
      <p>Through DARE UK funding, we developed TRE-FX, a rapid prototype leveraging GA4GH Task
        Execution Service (TES) for federated analysis. Originally designed for genomics, we
        extended TES to diverse data types and environments. TRE-FX supports complex workflows while
        integrating SQL and GraphQL to simplify adoption. Wizard-driven interfaces and API access
        further enhance usability, enabling seamless execution of federated queries across secure
        environments.</p>
    </sec>
    <sec>
      <title>Results</title>
      <p>TRE-FX establishes a hub-and-spoke configuration for secure data access. Safe Settings,
        Projects, and People ensure controlled access to Safe Data, with results passing through an
        airlock for authorized release. Open-sourced and backed by further investment, TRE-FX will
        evolve into a national, cross-domain solution. Transparency is a core principle, with public
        visibility of projects, participants, and queries fostering trust. This commitment will
        expand in the next development phase.</p>
    </sec>
    <sec>
      <title>Conclusion</title>
      <p>TRE-FX delivers an end-to-end federated analysis solution within nine months, spanning
        three institutions. By integrating accessible tools like SQL, we support diverse research
        needs. Future phases will enhance reproducibility with RO-Crates and explore FAIR federated
        analytics. This initiative drives national dialogue, shaping the future of federated
        research in the UK.</p>
    </sec>
  </body>
</article>