<?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="research-article">
<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.v11i5.3695</article-id>
<article-id pub-id-type="publisher-id">11:5:3695</article-id>
<article-id pub-id-type="pii">S2399490821036958</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Population Data Science</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Enhancing data quality and usability – collaboration between data owners and researchers</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author"><name><surname>Macintyre</surname><given-names initials="C">Cecilia</given-names></name><xref ref-type="aff" rid="affil-1"><sup>1</sup></xref></contrib>
<contrib contrib-type="author"><name><surname>Treanor</surname><given-names initials="M">Morag</given-names></name><xref ref-type="aff" rid="affil-2"><sup>2</sup></xref></contrib>
<contrib contrib-type="author"><name><surname>Behrens</surname><given-names initials="S">Silvia</given-names></name><xref ref-type="aff" rid="affil-2"><sup>2</sup></xref></contrib>
<contrib contrib-type="author"><name><surname>Russell</surname><given-names initials="E">Emma</given-names></name><xref ref-type="aff" rid="affil-2"><sup>2</sup></xref></contrib>
<contrib contrib-type="author"><name><surname>Lee-Shield</surname><given-names initials="B">Bethany</given-names></name><xref ref-type="aff" rid="affil-3"><sup>3</sup></xref></contrib>
<contrib contrib-type="author"><name><surname>Williamson</surname><given-names initials="L">Lee</given-names></name><xref ref-type="aff" rid="affil-3"><sup>3</sup></xref></contrib>
<contrib contrib-type="author"><name><surname>Troncoso</surname><given-names initials="P">Patricio</given-names></name><xref ref-type="aff" rid="affil-3"><sup>3</sup></xref></contrib>
<aff id="affil-1"><label>1</label><institution>Scottish Government, Edinburgh, United Kingdom</institution></aff>
<aff id="affil-2"><label>2</label><institution>University of Glasgow, Glasgow, United Kingdom</institution></aff>
<aff id="affil-3"><label>3</label><institution>University of Edinburgh, Edinburgh, United Kingdom</institution></aff>
</contrib-group>
<pub-date date-type="pub" publication-format="electronic"><day></day><month></month><year></year></pub-date>
<pub-date date-type="collection" publication-format="electronic"><year></year></pub-date>
<volume>11</volume>
<issue>5</issue>
<elocation-id>3695</elocation-id>
<permissions>
<license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by-nc-nd/4.0/">
<license-p>This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.</license-p>
</license>
</permissions>
<self-uri xlink:href="https://ijpds.org/article/view/3695">This article is available from the IJPDS website at: https://ijpds.org/article/view/3695</self-uri>
<abstract>
<p>Administrative Data Research (ADR) Scotland is a partnership between Scottish Government and the Scottish Centre for Administrative Research funded by Economic and Social Research Council. Together we are transforming how public sector data in Scotland is curated, accessed and analysed to unlock its full potential for policymakers and the public. This talk will illustrate the benefits of collaboration between data owners and researchers in providing advice on analysis and creating resources for the wider research community. The focus is a research project that explores context, factors and approaches to educational exclusions and absences using a large linked longitudinal administrative data set as an exemplar. The dataset spans 2008–2019 and combines multiple sources: Education data from the Scottish Government(school census, qualifications, absence, exclusions and school leaver destinations) Health datasets (Prescribing Information System and Scottish Morbidity Records) Census data (2001 &amp; 2011) The project team combined both academic colleagues and a member of the Scottish Government which resulted in impact achieved by addressing data issues which arose during analysis, supplying code used in analysis of official statistics and expansion of the supporting documentation. The talk will highlight: How collaboration between government and academia enhances data quality and usability for both research and statistical use Supporting resources developed for researchers, including user guides, data dictionary and ‘Data Explained’ documents—an output that exemplifies the value of close collaboration between data owners and researchers.</p>
</abstract>
</article-meta>
</front>
</article>