At ONA14 in Chicago in late September we unveiled the new OpenElections data download interface. We presented at the Knight Foundation’s Knight Village during their office hours for featured News Challenge projects, as well as during a lighting talk. OpenElections’ Geoff Hing and Sara Schnadt showed off their handiwork based on in-depth discussions and feedback from many data journos. The crowd at ONA was receptive, and the people we talked to were keen to start having access to the long awaited data from the first few states.
As you can see from the data map view above, there are only three states that have data available so far. These are Maryland, West Virginia and Wyoming, for which you can download ‘raw’ data. For our purposes, this means that you can get official data at the most common results reporting levels, with the most frequently used fields identified but without any further standardization. We will have ‘raw’ data on all the states in the next few months, and will work on having fully cleaned and standardized data on all the states after this initial process is complete.
As things progress, you will see updates to both the map view and the detailed data view where you can see the different reporting levels that have data ready for download so far.
A pink download icon indicates available data, and a grey icon indicates that data exists for a particular race at a particular reporting level, but that we don’t yet have it online.
The race selection tool at the top of the page includes a visualization that gives an overview of all the races in our timespan, and a slider for selecting a date range to review races in the download table. For states like Maryland (shown in the full page-view above), there are only two races every two years so this slider isn’t so crucial, but for states like Florida (directly above), this slider can be useful.
We encourage you to take the interface for a spin, and tell us what you think! And, if you would like to help us get more data into this interface faster, and you are fairly canny with Python, we would love to hear from you. You can learn more about what this would entail here.