Demand-Driven Open Data (DDOD) is a framework of tools and methodologies to provide a systematic, ongoing and transparent mechanism for you to tell public data owners what's most valuable.
All work is entered, prioritized, implemented, and validated in the form of "use cases". This approach allows for all projects to have a known value even before work begins. It is the Lean Startup approach to open data initiatives.
Use Cases
Use cases initially get entered and discussed in as Github issues (github.com/demand-driven-open-data/ddod-intake/issues) and linked to related wiki entries
Specifications
Detailed specifications for each use case are described in the intake wiki (github.com/demand-driven-open-data/ddod-intake/wiki) and linked to related issue entries
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Data Users
This document is intended for data users. That could include anyone in industry, academia, nonprofits or even other government orgs who could benefit from DDOD.
Data Owners
This document is indended for the other side of this marketplace, the data owners. It's for use by government agencies and program managers to learn how DDOD could benefit their organizations.