Establishing a Data Trust: From Concept to Reality


Blog by Stefaan Verhulst, Aditi Ramesh & Andrew Young, Peter Rabley & Christopher Keefe: “As ever-more areas of our public and private lives succumb to a process of datafication, it is becoming increasingly urgent to find new ways of managing the data lifecycle: how data is collected, stored, used, and reused. In particular, legacy notions of control and data access need to be reimagined for the twenty-first century, in ways that give more prominence to the public good and common interests – in a manner that is responsible and sustainable. That is particularly true for mapping data which is why The GovLab and FutureState, with the support of The Rockefeller Foundation, are partnering with PLACE to assist them in designing a new operational and governance approach for creating, storing and accessing mapping data: a Data Trust. 

PLACE is a non-profit formed out of a belief that mapping data is an integral part of the modern digital ecosystem and critical to unlocking economic, social and environmental opportunities for sustainable and equitable growth, development and climate resiliency; however, this data is not available or affordable in too many places around the world. PLACE’s goal is to bridge this part of the digital divide.

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Five key considerations inform the design of such a new framework:

  • Governing Data as a Commons: The work of Elinor Ostrom (among others) has highlighted models that go beyond private ownership and management. As a non-excludable and non-rivalrous asset, data fits this model well: one entity’s control or “ownership” of data doesn’t limit another entity’s (non-excludable); and one entity’s consumption or use of data doesn’t prevent another entity from similarly doing so (non-rivalrous). A new framework for governance would emphasize the central role of  “data as a commons.”
  • Avoiding a “Tragedy of the Commons”: Any commons is susceptible to a “tragedy of the commons”: a phenomenon in which entities or individuals free-ride on shared resources, depleting their value or usability for all, resulting in a failure to invest in maintenance, improvement and innovation and in the process contributing negatively to the public interest . Any reimagined model for data governance needs to acknowledge this risk, and build in methods and processes to avoid a tragedy of the commons and ensure “data sustainability.” As further described below we believe that sustainability can best be achieved through a membership model.
  • Tackling Data Asymmetries and Re-Distribution of Responsibilities: Everyone is a participant in today’s “data commons,” but not all stakeholders benefit equally. One way to ensure the sustainability of a data commons is to require that larger players—e.g., the most profitable platforms, and other entities that disproportionately benefit from network effects—assume greater responsibilities to maintain the commons. These responsibilities can take many forms—financial, technical know-how, regulatory or legal prowess—and will vary by entity and each entity’s specialization. The general idea is that all stakeholders should have equal rights and access—but some will have greater responsibilities and may be required to contribute more.
  • Independent Trustees and Strong Engagement: Who should govern the data as a commons? Another way to avoid a tragedy of the commons is to ensure that a clear set of rules, principles and guidelines determine what is acceptable (and not), and what constitutes fair play and reasonable data access and use. These guidelines should be designed and administered by independent trustees, whose responsibilities, powers, terms and selection mechanisms are clearly defined and bounded. The trustees should be drawn from across geographies and sectors, representing as wide a range of interests and expertise as possible.In addition, trustees should steer responsible data access in a manner that is informed by input from experts, stakeholders, data subjects, and intended beneficiaries, using innovative ways of engagement and deliberations.
  • Inclusion and Protection: A data trust designed for the commons must “work” for all and especially the most vulnerable and marginalized among us. The identity of some people and communities is inextricably linked to location and, therefore, requires us to be especially mindful of the risks of abuse for such communities. How can we prevent surveillance or bias against indigenous groups, for example? Equally important, how can we empower communities with more understanding of and voice in how data is collected and used about their place? Such communities are front-and-center in the design of the Trust and its governance….(More)”.