Skip to content

Tools for consolidation and analysis of raw election results from the most reliable sources -- the election agencies themselves.

License

Notifications You must be signed in to change notification settings

ElectionDataAnalysis/electiondata

Repository files navigation

CII Best Practices

Overview

This repository provides tools for consolidation and analysis of raw election results from the most reliable sources -- the election agencies themselves.

  • Consolidation: take as input election results files from a wide variety of sources and load the data into a relational database
  • Export: create consistent-format export files of results sets rolled up to any desired intermediate geography
    • tabular (tab-separated text)
    • xml (following NIST Election Results Reporting Common Data Format V2)
    • json (following NIST Election Results Reporting Common Data Format V2)
  • Analysis:
    • Curates one-county outliers of interest
    • Calculates difference-in-difference for results available by vote type
  • Visualization:
    • Scatter plots
    • Bar charts

Target Audience

This system is intended to be of use to news media, campaigns, election officials, students of politics and elections, and anyone else who is interested in assembling and understanding election results. If you have ideas for using this system or if you would like to stay updated on the progress of this project, we'd like to hear from you.

How to use the app

See documentation directory, which includes

How to Contribute Code

See CONTRIBUTING.MD.

Contributors

  • Stephanie Singer, Hatfield School of Government (Portland State University), former Chair, Philadelphia County Board of Elections
  • Janaki Raghuram Srungavarapu, Hatfield School of Government (Portland State University)
  • Eric Tsai, Hatfield School of Government (Portland State University)
  • Todd Graham, Hatfield School of Government (Portland State University)
  • Bryan Loy
  • Jon Wolgamott
  • Elliot Meyerson

Copyright

Copyright (c) Portland State University 2021

Funding

Funding provided October 2019 - November 2021 by the National Science Foundation

  • Award #1936809, "EAGER: Data Science for Election Verification"
  • Award #2027089, "RAPID: Election Result Anomaly Detection for 2020" Data collection and consolidation for the 2020 US General Election funded in part by the Verified Voting Foundation.

License

See LICENSE.md

About

Tools for consolidation and analysis of raw election results from the most reliable sources -- the election agencies themselves.

Topics

Resources

License

Code of conduct

Stars

Watchers

Forks

Packages

No packages published

Languages