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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.v11i5.3467</article-id>
<article-id pub-id-type="publisher-id">11:5:3467</article-id>
<article-id pub-id-type="pii">S2399490821034674</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Population Data Science</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Defending the Data Access Spectrum</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author"><name><surname>Welpton</surname><given-names initials="R">Richard</given-names></name><xref ref-type="aff" rid="affil-1"><sup>1</sup></xref></contrib>
<contrib contrib-type="author"><name><surname>Ritchie</surname><given-names initials="F">Felix</given-names></name><xref ref-type="aff" rid="affil-2"><sup>2</sup></xref></contrib>
<contrib contrib-type="author"><name><surname>Sanchez</surname><given-names initials="A">Aida</given-names></name><xref ref-type="aff" rid="affil-3"><sup>3</sup></xref></contrib>
<contrib contrib-type="author"><name><surname>Magder</surname><given-names initials="C">Cristina</given-names></name><xref ref-type="aff" rid="affil-4"><sup>4</sup></xref></contrib>
<contrib contrib-type="author"><name><surname>Varley-Winter</surname><given-names initials="O">Olivia</given-names></name><xref ref-type="aff" rid="affil-5"><sup>5</sup></xref></contrib>
<aff id="affil-1"><label>1</label><institution>UKRI: Economic and Social Research Council, London, United Kingdom</institution></aff>
<aff id="affil-2"><label>2</label><institution>University of the West of England, Bristol, United Kingdom</institution></aff>
<aff id="affil-3"><label>3</label><institution>University College London, London, United Kingdom</institution></aff>
<aff id="affil-4"><label>4</label><institution>University of Essex, Colchester, United Kingdom</institution></aff>
<aff id="affil-5"><label>5</label><institution>Smart Data Research UK, London, 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>3467</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/3467">This article is available from the IJPDS website at: https://ijpds.org/article/view/3467</self-uri>
<abstract>
<p>We map the Data Access Spectrum to the Five Safes to provide a framework that maximises use of individual-level data, helping us to safely share population data for research, according to the data’s risk profile. The Trusted Research Environment (TRE) has been the success story of data access this century. By providing highly secure access, TREs enable researchers to safely make use of the most sensitive data. But the Scientific Use File (SUF) remains the workhorse of academic research. SUFs are downloadable files made available under licence to authorised users. Access to these data allows researchers to undertake population research which doesn’t involve the sensitive, detailed data available in TREs; they are accessible to users who cannot access TREs (such as students and overseas researchers), while the research can take place at lower cost. The UK Data Service reports that the volume of use of SUFs significantly exceeds that of their TRE. The fear that new technologies could reverse engineer the de-identified records in SUF data have led to suggestions that all individual-level research data should only be available through TREs. Restricting all population data research to TREs (a data access spectrum polarised between closed (TRE) and open (aggregated) data) is undesirable. We seek to rebalance the debate by focusing on benefits that support providing access to SUFs under license, and how stakeholders assess the risk versus utility of that data. From this we draw conclusions for the future of data access.</p>
</abstract>
</article-meta>
</front>
</article>
