Now that we are a ways into our "Election Night Reporting System" project, we want to start sharing some of what we are learning.  We had talked about a dedicated Wiki or some such, but our time was better spent digging into the assignment graciously supported by the Knight Foundation Prototype Fund.  Perhaps the best place to start is a summary of what we've been saying within the ENRS team, about what we're trying to accomplish. First, we're toying with this silly internal project code name, "ENRS" and we don't expect it to hang around forever. Our biggest grip is that what we're trying to do extends way beyond the night of elections, but more about that later.

Our ENRS project is based on a few assumptions, or perhaps one could say some hypotheses that we hope to prove. "Prove" is probably a strong word. It might better to say that we expect that our assumptions will be valid, but with practical limitations that we'll discover.

The assumptions are fundamentally about three related topics:

  1. The nature and detail of election results data;
  2. The types of software and services that one could build to leverage that data for public transparency; and
  3. Perhaps most critically, the ability for data and software to interact in a standard way that could be adopted broadly.

As we go along in the project, we hope to say more about the assumptions in each of these areas.

But it is the goal of feasible broad adoption of standards that is really the most important part. There's a huge amount of latent value (in terms of transparency and accountability) to be had from aggregating and analyzing a huge amount of election results data. But most of that data is effectively locked up, at present, in thousands of little lockboxes of proprietary and/or legacy data formats.

It's not as though most local election officials -- the folks who are the source of election results data, as they conduct elections and the process of tallying ballots -- want to keep the data locked up, nor to impede others' activities in aggregating results data across counties and states, and analyzing it. Rather, most local election officials just don't have the means to "get the data out" in way that supports such activities.

We believe that the time is right to create the technology to do just that, and enable election officials to use the technology quickly and easily. And this prototype phase of ENRS is the beginning.

Lastly, we have many people to thank, starting with Chris Barr and the Knight Foundation for its grant to support this prototype project. Further, the current work is based on a previous design phase. Our thanks to our interactive design team led by DDO, and the Travis County, TX Elections Team who provided valuable input and feedback during that earlier phase of work, without which the current project wouldn't be possible.

-- EJS