Governing the Environment-Related Data Space

This piece, written by Stefaan G. Verhulst, Anthony Zacharzewski and Christian Hudson, was originally published on the Data & Policy Blog. Data & Policy is a peer-reviewed, open access journal dedicated to the impact of data science on policy and governance. To learn more, please visit

Photo by Guillaume de Germain on Unsplash

Today, The GovLab and The Democratic Society published their report, “Governing the Environment-Related Data Space”, written by Jörn Fritzenkötter, Laura Hohoff, Paola Pierri, Stefaan G. Verhulst, Andrew Young, and Anthony Zacharzewski . The report captures the findings of their joint research centered on the responsible and effective reuse of environment-related data to achieve greater social and environmental impact.

Environment-related data (ERD) encompasses numerous kinds of data across a wide range of sectors. It can best be defined as data related to any element of the Driver-Pressure-State-Impact-Response (DPSIR) Framework. If leveraged effectively, this wealth of data could help society establish a sustainable economy, take action against climate change, and support environmental justice — as recognized recently by French President Emmanuel Macron and UN Secretary General’s Special Envoy for Climate Ambition and Solutions Michael R. Bloomberg when establishing the Climate Data Steering Committee.

While several actors are working to improve access to, as well as promote the (re)use of, ERD data, two key challenges that hamper progress on this front are data asymmetries and data enclosures. Data asymmetries occur due to the ever-increasing amounts of ERD scattered across diverse actors, with larger and more powerful stakeholders often maintaining unequal access. Asymmetries lead to problems with accessibility and findability (data enclosures), leading to limited sharing and collaboration, and stunting the ability to use data and maximize its potential to address public ills.

The risks and costs of data enclosure and data asymmetries are high. Information bottlenecks cause resources to be misallocated, slow scientific progress, and limit our understanding of the environment.

A fit-for-purpose governance framework could offer a solution to these barriers by creating space for more systematic, sustainable, and responsible data sharing and collaboration. Better data sharing can in turn ease information flows, mitigate asymmetries, and minimize data enclosures.

And there are some clear criteria for an effective governance framework. It must have a clear organizing purpose, so as to ensure that data projects are pursued with consideration for the broader technical, social, political, and economic contexts within which the data is produced and consumed. Ensuring that the framework adheres to the three “3 Ps” of governance–principles, processes, and practices–is essential. Principles are important as they offer a “North Star” for a governance framework, ensuring that all activities are aligned with certain commonly agreed criteria. Governance processes enshrine systematic mechanisms for making and implementing decisions. And finally, practices operationalize governance and ensure the principles are upheld and processes are undertaken in reality.

The 3 Ps of Data Governance by Stefaan G. Verhulst and Andrew Young

A purpose-driven approach, informed by the “3 Ps,” suggests four plausible options for ERD governance models that could be established in the short term. The remainder of this blog examines these four options.

Laissez-Faire: No action; self-organization of the data space

The status quo is of non-governance, and the laissez-faire approach upholds this. In this system, a shared data space operates without oversight and coordination at the operational level. Instead, strategic decision-making and lower-level governance are done by individual data providers in negotiation with data users. Collective action on the global scale is limited. It can be argued that this approach allows for greater agility and efficiency, however this is not always truly the case.

Emerging Lead: Existing organization with relevant interests in the area expands its mandate and uses its current governance structures

A number of organizations are currently attempting to create sectoral data spaces to share ERD. It is conceivable that a single entity could be well-positioned to federate organizations under a single governance structure. Strategic decision-making and lower-level governance rule-setting and process rules would then be undertaken by a governance committee or others in negotiation with data users.

New Traditional Organization: Creation of a governing institution de novo

As the name suggests, this model calls for the creation of an entirely new structure, with governance principles and structures designed from scratch. The founding members would be responsible for establishing decision making norms and lower-level governance rule-setting processes. The levels of stakeholder involvement and consultation would also depend largely on the decisions of the founding members. One risk with such a model is an imbalance in representation and power.

New Collaborative: New structure based on participatory governance tailored to context and decision-making needs

The most promising model would see partners create an entirely new structure and build governance principles and processes from scratch. It diverges from the new traditional organization model in terms of its broader stakeholder engagement, where strategic decision making and lower-level governance rule-setting and process rules setting is agreed upon by founding members with a broad and significant stakeholder involvement. This means that stakeholders collaborate closely and co-decide. In certain cases, independent trustees may be empowered to oversee this governance framework to ensure equitable access and to mediate disputes.

The ERD ecosystem is a fast-moving area. To begin prototyping an effective data collaborative governance structure in the space will require rapid action. Moving forward, three approaches that can be used to craft fit-for-purpose principles, processes and practices are: developing principles through participatory processes; designing processes for collaborative governance; and creating practices and tools to de-risk collaboration.

The full report (PDF) is available HERE.

About the Authors:

Stefaan G. Verhulst is Data & Policy Editor-in-Chief and Co-Founder, Chief R&D Officer, and Director of the Data Program of the Governance Laboratory (The GovLab) at New York University.

Anthony Zacharzewski is President and Founder of The Democratic Society.

Christian Hudson is Lead for European Union G7 and G20 Environmental Diplomacy Support.



Responsible Data Leadership to Address the Challenges of the 21st Century

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store