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EAVS Section B Data Standard

About the project

Developed through a collaborative agreement between the Council of State Governments and the Federal Voting Assistance Program, or FVAP, the Election Administration and Voting Survey (EAVS) Section B Data Standard aims to reduce the amount of work required for election officials to complete the EAVS, a bi-annual survey administered by the US Election Assistance Commission, or EAC. A data export, based on voter-level transactional data, can be compiled to answer the questions in Section B as well as provide more comprehensive information for analysis.

Documentation

Prerequisites

The documentation is built with Sphinx and requires execution of a simple python script. Packages are maintained with pipenv, which can be installed with pip.

Changing branch name

If you have an existing clone of the respository, you'll need to update the branch name to main from master. To do this, run the following commands:

git branch -m master main
git fetch origin
git branch -u origin/main main
git remote set-head origin -a

Build

Navigate to the project directory (assuming you're not already there) and install the required libraries.

cd /path/to/esb-data-standard
pipenv install

If you've made changes to the specification, do the following:

cd docs
pipenv run python tableschema_docs_parser.py

After executing the above (or assuming you haven't made changes), navigate to the docs folder and run the following commands:

sphinx-build -b html source build
python -m http.server --directory build

Open a browser and connect to http://localhost:8000 and you should see the documentation.

Publishing a new release

When publishing a new release, double-check that there are no errors in the tableschema, the version numbers are correct in tableschema.json and conf.py, the documentation contains no build errors, and the documentation is viewable locally using the steps defined above.

When creating a GitHub release, make sure to explicitly add the latest tableschema.json to the release so implementers of the standard can easily access the file to use to validate their standardized datasets using the DataCurator.