Creating a scalable model to improve government open data

Summary

The challenge

Following implementation of the White House’s Open Data Policy, federal agencies produced thousands of open datasets. However, many were incomplete, inconsistently formatted, or difficult to integrate into applications.

As a result, much of this data remained underutilized. Improving and maintaining datasets at scale exceeded the capacity of individual agencies, creating a need for a new model that could expand access and usability without relying solely on government resources.

The solution

Adopta.Agency introduced a civic crowdsourcing model for improving government open data.

At the center of this model was an open blueprint process that guided contributors through structured steps to improve a dataset. Participants could incrementally increase value — first by cleaning and structuring data into JSON, and then by transforming it into a fully functional API.

The model leveraged GitHub as a collaboration platform, enabling distributed contributors to work transparently and iteratively on shared datasets.

With support from the Knight Foundation, a prototype was developed and applied to five federal datasets. This work produced a set of reusable blueprint patterns that others could follow to replicate and scale dataset improvements across government.

The results

• Secured grant funding from the Knight Foundation to support development and prototyping
• Designed and launched the Adopta.Agency blueprint process for improving open datasets
• Applied the model to five federal datasets, including the U.S. Federal Budget, Veterans Affairs Open Data Portal, Department of Education Tech Data, My Brother’s Keeper, and ClinicalTrials.gov
• Created five reusable blueprint patterns that enabled others to replicate and scale dataset improvements