Design Action Research with Government
Design Action Research with Government (DARG) is a guide for creating civic innovation projects.
The goal of the DARG framework is to build productive and sustainable ways of working together for:
- governments
- research institutions, and
- local community groups.
We based the framework on years of successful cooperation between the City of Boston and the Engagement Lab at Emerson College. The guide goes over the building of partnerships, analyzing results, and iterating on projects.
Why we did this
More cities across the country are focused on the importance of civic innovation. We believe putting the right process in place makes it easier to build and develop products. Cities also gain information that is shareable, scalable, and can make an impact.
The Engagement Lab and New Urban Mechanics wanted to document the nature of our shared approach. We hoped to help other cities build on what we had learned.
The experiment
Our hypothesis? Putting what we’ve learned into a guidebook will lead to more effective and successful experiments in Boston and beyond. We would create the DARG guidebook in a format that allowed other innovators to apply to their own situations.
Tailor an experiment to fit the unique needs of the issue being addressed by:
- finding the right partner organizations
- aligning goals
- asking the right questions, and
- designing an experiment that can be tweaked and repeated in an iterative process.
With this approach, even if a project fails to achieve the stated goals, it will still be a valuable source of data and experience. This could help future experiments and act as a stepping stone for a work with partner groups.
Results and lessons learned
The DARG guide principles helped drive our most effective partnerships over the course of many years. Work with the Engagement Game Lab, which began with the Hub2 project in 2008, developed into long-term, iterative experiments. These include Hub2, Participatory Chinatown, and Community PlanIt to Habit@.
While the guide is a good start, we expect the model to evolve as we do more iterative and collaborative work with research institutions.