Data Collaboratives: A Logical Next Step for Local Government Open Data Initiatives?

I have a theory: As the local government open data movement continues to mature and cities look for new ways to leverage their investments in this space, data collaboratives will provide a compelling path forward.

Before we dig into this a bit more, let’s spend a minute defining the term data collaborative, since there isn’t really a standard definition (For further reading on defining the term data collaborative, see datacollaboratives.org, an initiative run out of GovLab, and Data-Driven Detroit’s blog on the Metro Detroit Data Alliance). At a basic conceptual level, a data collaborative is a cross-sector group of organizations who come together around a centralized data platform that is managed by a trusted intermediary (typically a non-profit or academic institution) and is designed to facilitate data sharing and analytics to achieve a specific goal. Within the context of civic tech, the goal is generally around social impact. Put more simply, data collaboratives are comprised of three things: a group of organizations willing to share data, a centralized data platform, and a common goal or set of goals.  

Municipal open data platforms are essentially data collaboratives housed within a city; they are data collaboratives where the contributing stakeholders are city agencies. Often, however, one important component is missing, and that is the cross-sector collaboration and engagement that drives meaningful outcomes.

Over the past several years, cities have made (often significant) investments in open data platforms and initiatives. In my experience, the most significant returns on these investments have been primarily internal facing (though they certainly result in external benefits, such as improved services). Open data has led cities to manage, use, and share data internally on a wider scale, more efficiently. It has increased data literacy among city staff. It has uncovered operational inefficiencies and led to important discussions about how to fix them. It has also led to many conversations about impact, performance measurement, and data-driven decision making. These are very important—and often highly impactful—benefits.

Open data has also been an external force for good. It has improved transparency (though I’d argue it’s not a panacea for government transparency), it has mobilized communities, and in some places has contributed to solving community problems in interesting ways. But it’s also true that in some places it hasn’t done much at all. And even when it has, the impact in the community seems to have been rather modest. I suspect this is mostly attributable to a relatively thin population of qualified users with sufficient capacity and resources to leverage open data in a truly substantive way. But, I believe data collaboratives hold significant progress in overcoming this challenge.

The data collaborative model addresses the capacity gap in several ways. First, it mobilizes organizations around a common goal or set of goals (this may sound familiar to collective impact enthusiasts). Collective impact initiatives can be a very powerful force for change and can create political will to spend more time and resources on data and research. Second, it encourages organizations that might not otherwise engage in technology or data initiatives to come to the table. Data collaboratives require an organization with technical capacity to manage the technical heavy-lifting, but they don’t require all organizations to have this capacity. If one organization is in charge of managing the data, this frees up important resources in other organizations to do analysis and operationalize insights, and organizations that don’t have capacity to do anything data related can still benefit (and, importantly, contribute in other ways). Third, it encourages cross-sector collaboration, which I argue is important for solving virtually every significant community challenge of our time.

Regardless of any perceived shortcomings (real, or not) around open data’s direct community impact, there is still significant potential for cities to create it through their open data programs by moving toward community engagement and collaboration. In this regard, data collaboratives offer a promising mechanism. I suspect we’ll begin to see more cities and community groups rally around them as they consider ways to engage the community and extract additional value out of their investments in open data.  

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