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In recent years, smart city projects have made their way onto an increasing number of government agendas around the world. Smart cities use a combination of information and communication technologies, notably Internet of Things sensors, to provide improved services to their residents. Many of these projects, such as in Toronto, and in Manila, are built at least partially through public-private partnerships.

Critically, these cities get and stay “smart” by gathering large amounts of citizen data. But who manages that data? And is there a way to think about that question beyond just “us” versus “them”?

While the introduction of new technologies into our everyday lives should always be done with care, government-led projects like these are especially sensitive—when your city is the sole provider of many critical services, there is no opting out. Consequently, the rise of smart cities has created a parallel need for comprehensive, forward-thinking data governance solutions, especially as precedents continue to be set for what a smart city can and should look like.

Unfortunately, there is currently no clear protocol for the responsible governance of smart city data. Smart city projects too often have the nebulous goal of “efficiency,” with the needs of impacted communities taking a backseat to engineering concerns in the design process. This kind of organizational dilemma, involving multiple parties with different interests, is the perfect testing ground for a “commons” approach—an idea made famous by economist Elinor Ostrom for the community management of shared natural resources, and which could serve as a useful framework for data.

The term “commons” can mean a couple of different things when it comes to data governance. One is a commons platform—a kind of online repository that turns a collection of data into a shared resource. Such a platform is ideal for securely sharing datasets that provide a clear public benefit; Sage Bionetworks’ , for example, provides managed access to Alzheimer’s-related data and analyses.

However, there are many occasions where creating a data commons platform is neither feasible nor desirable. Consider, for instance, the issues that arose when a California city’s police force partnered with Amazon-owned Ring to in exchange for access to the camera footage. The dilemmas here, especially around who should be able to do what with the camera data, can’t be resolved through data sharing or building any kind of platform. Instead, they require an inclusive decision-making process and thoughtful questions around aligning data decisions with the community’s goals and values.

This is where a commons design approach comes in. Based on Ostrom’s , this framework provides an organizational strategy that allows resources—such as data—to be "managed by different communities in accordance with their unique rules, norms, and values.”

The first step in Ostrom’s commons design strategy is to define the community in play—a more challenging task than might be assumed. In a smart city, the “community” is first defined by geographic area—but how do you decide where the boundaries are drawn? Take the example of Washington, D.C. The District itself is part of a much larger metropolitan region that, despite being spread across three jurisdictions, functions in many ways like a single city. We could narrow it down to the area served by the metro system, but many people that aren’t on the metro line still come to D.C. for work or to access services. Major hospitals, for example, can create large virtual communities of people who don’t live or work in the area, but who nonetheless use city services and have elevated data privacy concerns. These communities aren’t defined solely by legal jurisdiction or state lines—so how should their needs slot into the city’s planning and decision making?

Once we delineate the community’s borders, the next step in Ostrom’s commons design process is to match the rules of governance to local needs and conditions. Too often, the conversation around data governance strategies jumps straight into the practical challenges of data collection and analysis. Instead, it’s important to step back and analyze why the smart region is being developed, what needs are being addressed through data, and how to balance conflicting values in different contexts. Efficiency and economic development are worthy goals, but not at the expense of autonomy, equity, security, and privacy. And while compromises are often necessary, it is critical that communities understand what is being traded—and that affected citizens be empowered to push for change they want to see.

In this context, a commons approach might help alleviate growing mistrust in these cities. The development of smart projects via public-private partnerships is contributing to a perception that the public square is increasingly governed by private technology companies—entities that cannot be trusted to act in the best interests of citizens. On the other hand, this wariness also extends to the public sector—nearly do not trust government agencies and service providers to protect their data. Where there is a lack of confidence in both markets and governments, there arises a need for more inclusive, community-driven governance. The commons, which was designed specifically to find a third way between the public and private, can provide a set of tools to meet this demand.

Applying a commons design approach to data governance allows us to flexibly manage data as society develops. Rather than fixating on who “owns” data, or looking at governance solely from a privacy lens, the commons helps us ensure that the needs of citizens are at the center of smart cities design.