Centering community involvement and equity across the data life cycle

Main Article Content

Amy Hawn Nelson
Sharon Zanti
Della Jenkins
Isabel Algrant

Abstract

Objectives
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 PAR conducted in the US from 2018-2025 to center equity in data access and use.


Methods
This Participatory Action Research (PAR) was convened by Actionable Intelligence for Social Policy (AISP) and resulted in a Toolkit (2025, 2020) and Workbook (2025). We first convened a workgroup of leaders from government agencies, CBOs, and advocates in 2018-2019. These findings informed the Equity in Practice Learning Community (EiPLC), 2022-2026, in which 2 cohorts of 10 sites implement data equity principles. In 2024-2025, a workgroup was convened to discuss updates and gaps from the original research with a focus on Tribal Data Sovereignty and demographic data standards (Race, Ethnicity, Language, Disability; Sexual Orientation and Gender Identity and Expression).


Results
The Toolkit and Workbook aim to support agencies seeking to acknowledge and compensate for the harms and bias baked into data and practice. The Toolkit presents foundations for community involvement and is organized across six stages of the administrative data life cycle—planning, data collection, data access, data analysis, use of algorithms and AI, and reporting and dissemination. The 2025 Toolkit includes updated guidance on participatory data governance, Tribal Data Sovereignty, and data standards. For each stage, the toolkit includes promising and problematic practices for centering equity in administrative data reuse, with over 50 site-based examples of work in action from across the US. The Workbook is based on the curriculum of the EiPLC, including activities that sites completed throughout their participation in the learning community.


Conclusion
Data integration can allow practitioners and policy-makers to address interconnected needs more effectively and holistically; however, benefit must outweigh risk. This collaboratively generated body of work outlines considerations and everyday actions for agencies and data practitioners to center equity in data practices in an accessible format.

Article Details

How to Cite
Nelson, A. H., Zanti, S., Jenkins, D. and Algrant, I. (2025) “Centering community involvement and equity across the data life cycle”, International Journal of Population Data Science, 10(4). doi: 10.23889/ijpds.v10i3.3025.

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