The Use of Data Trusts to Improve Impact (Responsibly)
Governments, communities, academic institutions, and organizations in the social sector have long-desired to collaborate with other organizations within their networks by using shared data to better address important societal issues or to more fully inform policy or funding decisions.

Governments, communities, academic institutions, and organizations in the social sector have long-desired to collaborate with other organizations within their networks by using shared data to better address important societal issues or to more fully inform policy or funding decisions. These institutions know from experience that examining their own data in isolation not only creates programmatic and funding redundancies, but also limits the perspective and understanding of the challenges that they face.

When these organizations try to create data collaborations with others in their networks, however, they often discover additional challenges. First, each member of any given network has its own set of data definitions, measurements, formats, and time intervals. Second, members vary from one another in their technical capacities, as well as the technology systems they use to collect, secure, and share data, making data integration difficult and, at times, impracticable. Finally, members often find that the nature of cross-sector data sharing tends to be adversarial, with individual organizations’ legal staff engaging in an ongoing battle of red-lined drafts to manage risk and limit liability, seeking to answer needs and solve challenges that are specific only to their own organization.

BrightHive has seen firsthand the painful struggle that governments, communities, and academic institutions endure as they attempt to collaborate with one another. But we have also seen that when these networks deploy a solution that takes a more holistic approach — simultaneously addressing the legal, technical, and ongoing data governance challenges — networks are finally empowered to share data in a way that exponentially maximizes their individual and collective impact.

This solution is a data trust — a legal, technical, and governance framework that empowers a collective of organizations to securely connect their respective data sources and create new shared data resources that benefit each member.

Why do BrightHive data trusts work in ways that other data collaborations fail? They move beyond employing only one or two separate solutions and instead deploy an integrated framework in which the solutions to each challenge can be strategically aligned and mutually owned by all of the network’s members.

  1. Legal framework — BrightHive data trusts empower members of the trust to maintain ownership and control of their own data, agree with the other members about how data will be used (and who will use it) and formalize a legal framework that can be amended and evolve as the needs of the network grow and change.
  2. Technological platform — BrightHive data trusts provide the technology platform needed to ensure that data is shared securely and responsibly among its members and ensure interoperability between the members’ data systems. The combined data can then be used to compute new values, such as outcomes, for the data trust members to use.
  3. Governance — BrightHive data trusts establish a governing body to monitor and sustain the data trust over time.

When these three keys are in place, new data connections and “pooled” data resources are created, allowing organizations to better coordinate action, measure their impact, quickly answer emerging questions and be more responsive to the current and future information needs of their organizations, partners and communities.

At BrightHive, we are excited by the ways we have seen data trusts unlock new levels of impact for organizations and their networks. But as a public benefit corporation, we think the value of data trusts can and should extend even further, benefiting the public good. BrightHive data trusts are designed to improve equity of opportunity and provide access and use of the data trusts to organizations, networks, and communities that might not normally participate in data collaboratives due to institutional or contextual constraints. This is especially true for organizations, networks and communities that serve individuals and groups that are historically underserved or underrepresented, or those that may have limited resources, do not possess fully integrated data systems, or lack the necessary data or technology expertise on staff.

If we truly want to achieve the most combinatorial value of collective data and serve those that can benefit from data, then we need to make sure that all data providers, and the communities where they work, are able to participate.


Use of open source technology — BightHive data trusts utilize open source technology that is freely available to individuals and organizations to view, edit, and use.. This eliminates the need for organizations to purchase or adopt a new system in order to participate. The application programming interface (API) used to connect to each organization’s data system(s) and the extraction, transfer, and load (ETL) algorithms used to pull data into the data trust can be used on their existing data system(s) without significant disruption to existing structures and procedures and without additional burden on staff or partners.

Flexible and modular architecture — Typical data collaborations often take a one-size-fits-all approach to the technical architecture. This will not work for data collaborations in which data providers possess distinct technical structures and procedures, as well as their own requirements for data privacy and security. BrightHive’s data trusts provide a flexible and modular architecture stack to meet the challenges and requirements of the individual data providers, including the ability to configure the data trust to account for limitations or constraints in how data is integrated, especially the personally identifiable data needed to link data sets. The flexibility and modularity of BrightHive data trusts also provide a critical connection for organizations, networks and communities that might need additional infrastructure to overcome their own limited systems or infrastructure.

Ownership of data — BrightHive data trusts enable data trust members to own and control their individual and collective data, allowing the data providers to dictate how their data is used, and by whom. The data trust members also control their combined data — the “pooled resources” — so that collectively they can decide how these resources may be used. This approach deviates from other types of data collaborations in which one party — usually a funder or government — takes ownership of the combined data and often dictates who can use it and how it is used. The BrightHive structure levels the playing field for all data providers and democratizes the data so that all may contribute and benefit from its combinatorial value.

Leverage existing tools, partnerships, and collaborations — BrightHive data trusts harness the power of organizations, networks and communities that already know the context and history of their area of work, as well as the existing data and technology to draw upon. This enables BrightHive to design, develop and deploy a data trust that will meet well-known needs within their specific context, reduce costs and alleviate redundancies within their area.

As more and more networks seek to combine their data to address important societal issues or to more fully inform policy or funding decisions, it will be critical for them to do so in a manner that is not only responsible and sustainable, but also equitable so that each network’s members maintain ownership and control of their own data. BrightHive is helping networks across the country achieve these goals through data trusts and working daily to create more connected and collaborative data communities.