Recommendations for Improving Election Data Transparency

The report argues that decentralized election administration in the US has created a patchwork of transparency policies that can undermine democratic legitimacy and disproportionately affect marginalized communities. It provides specific recommendations for improving the accessibility and accuracy of voter files, the transparency of ballot processing and tracking, and the implementation of robust ballot curing and risk-limiting audit procedures.

• Voter registration files frequently contain errors and missing information, which can lead to eligible voters being excluded from elections. A 2012 Pew Center report estimated there were 24 million voter registration inaccuracies across US states.
• Voters of color are disproportionately affected by voter roll purges. A national study from November 2020 to July 2021 found that a majority of counties with the most aggressive purges disproportionately removed people of color.
• The implementation of ballot tracking technology is associated with lower ballot rejection rates. States that had ballot tracking during the 2020 general election had lower rejection rates than the national average.
• Precinct-level election data is often difficult to access in analyzable formats, with fewer than half of US states sharing these results in machine-readable data files.
• Ballot curing policies—which allow voters to fix errors on mail-in ballots—reduce rejection rates. In 2020, states with curing policies had an average rejection rate of 0.79 percent, compared to 0.84 percent in states without such policies.
• Risk-limiting audits (RLAs) are considered a best practice for post-election tabulation because they use a preset risk limit to ensure the correct winner is certified, but they are not yet widely required by law. As of 2022, only Colorado, Rhode Island, and Virginia required RLAs by law.
• Inadequate funding for state and local election offices serves as a significant barrier to achieving data transparency, hindering the ability to upgrade databases, conduct audits, and train staff.

APA

Gordon-Rogers, L., Latner, M., & Williams, C. (2024). Recommendations for Improving Election Data Transparency. Union of Concerned Scientists. https://www.ucs.org/sites/default/files/2024-12/Recommendations-for-Improving-Data-Transparency_white-paper_1.pdf

Chicago

Gordon-Rogers, Liza, Michael Latner, and Christopher Williams. Recommendations for Improving Election Data Transparency. Union of Concerned Scientists, 2024. https://www.ucs.org/sites/default/files/2024-12/Recommendations-for-Improving-Data-Transparency_white-paper_1.pdf.

Wikipedia

{{cite report |last1=Gordon-Rogers |first1=Liza |last2=Latner |first2=Michael |last3=Williams |first3=Christopher |title=Recommendations for Improving Election Data Transparency |publisher=Union of Concerned Scientists |date=June 2024 |url=https://www.ucs.org/sites/default/files/2024-12/Recommendations-for-Improving-Data-Transparency_white-paper_1.pdf |access-date=23 October 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{gordonrogers2024recommendations, author = {Gordon-Rogers, Liza and Latner, Michael and Williams, Christopher}, title = {{Recommendations for Improving Election Data Transparency}}, institution = {Union of Concerned Scientists}, year = {2024}, month = jun, url = {https://www.ucs.org/sites/default/files/2024-12/Recommendations-for-Improving-Data-Transparency_white-paper_1.pdf}, urldate = {2026-10-23}, note = {Indexed by Climate Insights Directory} }