Data Federation Project
Federated data refers to data that are aggregated across a number of organizations, departments or agencies at various scales. Managing the volume, quality and completeness of data coming in from multiple sources is a common challenge for government agencies charged with collecting and maintaining domain-specific information. This project aims to address this challenge by providing ways to ingest data more easily, and provide real-time user feedback so that data contributors can make corrections before it is submitted to a central repository.
Federated data efforts are increasingly seen as an engine for transparency, economic growth, and accountability, yet collecting this kind of data remains a challenge. Despite the fact that efforts of this sort are increasing in frequency, each new effort is still improvising solutions in terms of processes, tooling, and compliance infrastructure.
It's time to take this problem seriously and invest in reusable tools and approaches that will streamline federated data efforts in the years to come.
- Interview notes
- Preliminary Findings
- US Data Federation Framework (includes Data Federation Maturity Model and Data Federation Playbook)
- Underway as of November 2018; Work can be tracked here, and ongoing updates can be found here.
- Project overview // PDF version
- Project overview with FNS case study // PDF version
- Project overview presentation // PDF version
- Webinar via Digital.gov on April 17, 2019 // Slides
There are several repositories that contain code that is a part of this project.