July 19, 2019 | Natalie Evans Harris
I’ve learned a few things about the power of data after nearly 20 years leading data capacity efforts in the Federal Government—more recently, under the Obama Administration, as well as co-founding a data technology company, BrightHive, in the private sector. Data can support transforming the human experience through our collective power. Data can inform insights and drive decisions that lead to a more equitable, representative society, creating opportunities for all to thrive. Finally, that Democracy is better when government, civic and private sectors come together.
For this vision to prevail, institutions and organizations must work collaboratively and responsibly to share their data with groups inside and outside of their network. To achieve this vision, a growing number of companies and government agencies are forming data partnerships to link data across institutional and geographic boundaries to support social good. Only when organizations take an integrated approach to addressing the legal, technical and governance challenges facing them will a truly meaningful outcome occur.
Meaningful outcomes with strong data practices as the foundation opens opportunities for understanding society and driving scalable impact. But as the role of the data scientist—in all its variations—has proliferated (we are the sexiest career of the 21st Century after all), the standards and practices for data governance, in particular, have not kept pace to build the consistencies necessary to trust data as a decision-maker and driver of innovative social change. Our data governance practices need to be improved by using robust frameworks that address major points of risk and ambiguity which typically prevent many actors from engaging in sharing.
Understanding traditional data sharing structures
Understanding traditional data sharing governance structures is key to improving these practices. Focused on protecting people by controlling the availability, usability, integrity and security of data, organizations traditionally establish clear rules for what data will be collected, how it will be stored, and who will have access to it. These rules are often centered around minimizing risk by setting controls and limiting access to data based on the user or the use case. In an environment where data is used for making funding decisions or evaluating programs, this model is ideal. It’s using internal data to evaluate internal activities.
But as data is increasingly used for drawing insights about society, the need to bring together diverse data sources is clear and it’s imperative that we move beyond data sharing as a short-term transaction to adopt rules that incentivize data sharing while minimizing barriers. These traditional data sharing governance structures tend to be:
- Short-sighted: Addressing only immediate needs using limited bilateral agreements without a plan for sustainability.
- Isolated: Sustained by a single champion but often failing due to changes in leadership or isolated engagement.
- Inequitable: Imposed on organizations which lack the capacity to participate on equal footing.
- Self-Interested: Lawyers protecting individual interests and eliminating liabilities at the expense of the value to all stakeholders.
Moving toward an improved framework for data sharing governance
Starting at this traditional governance baseline, data sharing governance is now expanding from practices incentivized solely by risk-based decisions to models with stability and equity of data collaborations at its foundation. This becomes crucial as more and more data is used to draw insights that drive marketing strategies, optimize internal practices, and enhance product development. It means CEOs and policymakers alike must balance individual’s trust that the needs for innovative solutions are balanced with the need to protect individual rights.
Following the European Union’s adoption of the General Data Privacy Regulation (GDPR), states such as California are defining rules for responsibly sharing data by strengthening individual data rights. This ultimately puts organizations on notice that how data is used matters more than the profits made from its use. To comply, organizations will need to demonstrate data sharing practices that are:
- Sustainable: Addressing immediate needs while at the same time supporting the potential for long-term growth.
- Coordinated: Supporting shared decision-making for trust-managed data resources and organizational data ownership.
- Equitable: Leveling the playing field for all data sharing members, regardless of size, capacity, or incentives to participate.
- Collaborative: Eliminating liability while creating value for communities and individuals who should benefit most from the data sharing.
As a Beeck Center Fellow, I’ve worked to define a sustainable model for data sharing governance that recognizes the needs of today and into the future. This model takes a more collaborative approach to establishing and managing governance practices. Through a series of interviews and research, collaborators define a process that starts with building coalitions around the policy problem, and taking stock of capacity, motivations, barriers, and potential data solutions. It leads to a governance framework designed with integrated feedback loops and focused on evaluating assumptions, approaches and measurable outcomes.
Recognizing that when government, civic and private sectors come together, democracy is better for it, the Digital Service Collaborative at Georgetown University’s Beeck Center and BrightHive will build a community of practice around this model to identify and develop best practices for collaborative data sharing governance. Our goal is to collaboratively advance the development and adoption of data sharing governance best practices leveraging the community of data and digital leaders in our network who are working on ways to responsibly share and use data to address some of society’s most challenging issues.
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The Digital Service Collaborative at the Beeck Center for Social Impact + Innovation is building a body of research around government data and digital services, creating tangible resources for practitioners, cultivating the community of data and digital service leaders in governments to share and scale efforts, and exploring policy considerations including ethics and privacy.
BrightHive helps organizations, networks and communities securely and responsibly link their data to enhance their impact, empower individual and collective decision making and increase equity of opportunity. BrightHive Data Trusts provide 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, empowering them to better coordinate action, measure their impact and be more responsive to the current and future information needs of their community.