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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.v11i5.3607</article-id>
<article-id pub-id-type="publisher-id">11:5:3607</article-id>
<article-id pub-id-type="pii">S2399490821036077</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Population Data Science</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>What Does it Look Like to Center Data Equity in 2025-2026 in the U.S.?</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author"><name><surname>Hawn Nelson</surname><given-names initials="A">Amy</given-names></name><xref ref-type="aff" rid="affil-1"><sup>1</sup></xref></contrib>
<contrib contrib-type="author"><name><surname>Jenkins</surname><given-names initials="A">Adelia</given-names></name><xref ref-type="aff" rid="affil-1"><sup>1</sup></xref></contrib>
<contrib contrib-type="author"><name><surname>Algrant</surname><given-names initials="I">Isabel</given-names></name><xref ref-type="aff" rid="affil-1"><sup>1</sup></xref></contrib>
<contrib contrib-type="author"><name><surname>Zanti</surname><given-names initials="S">Sharon</given-names></name><xref ref-type="aff" rid="affil-2"><sup>2</sup></xref></contrib>
<aff id="affil-1"><label>1</label><institution>University of Pennsylvania, Philadelphia, USA</institution></aff>
<aff id="affil-2"><label>2</label><institution>Iowa State University, Ames, USA</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>3607</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/3607">This article is available from the IJPDS website at: https://ijpds.org/article/view/3607</self-uri>
<abstract>
<p>Local and state governments routinely integrate data for public benefit, yet equity is rarely considered. This oversight raises concerns, as integrated data increasingly serve as the foundation for government action. This session shares insights from research conducted in the U.S. from 2018-2025 to center equity in data access and use. This participatory action research (PAR) was convened by Actionable Intelligence for Social Policy (AISP) and resulted in a Toolkit (2025, 2020) and Workbook (2025) widely used by government, community, and academic partners. The Toolkit and Workbook aim to support organizations seeking to acknowledge and compensate for the harms and bias baked into data and practice. In 2025, just before publication of the updates, the federal context in the United States changed drastically, posing new questions about how to center equity and protect those represented in the data. AISP chose not to amend our planned publication, despite widespread restrictions on the use of race explicit language. But in response to changes in the federal landscape, AISP also put together an informal memo to support state and local data practitioners in responding to the new federal administration and its priorities. The memo includes guidance and resources for accessing federal data, safeguarding state and local data, legal changes, data collection, methodological considerations, tracking and communicating changes, and advocacy. The memo, like the Toolkit and Workbook, has been a collaborative effort to respond to contemporary challenges. This session will discuss this changing context, and the implications for data practitioners working to center equity.</p>
</abstract>
</article-meta>
</front>
</article>