Environmental decision makers have a data plumbing problem. Data intermediaries can help.
At EPIC, we often hear about two fundamental problems from environmental decision-makers. They frequently tell us: I need more information! or, I’m drowning in data!—sometimes both. How can those realities coexist?
A big part of the challenge is that environmental data simply isn't flowing from where it’s gathered to where it’s needed. Many issues can prevent it from flowing, for instance: users might not know the data exists, it may not be in usable formats, it doesn’t get to users fast enough, or there’s a trust deficit preventing data from being shared or used altogether. To get key data moving, we need teams that are ready to fix the “plumbing” and remove the blockages—that’s where data intermediaries come in.
Comparing Data Flows
What do data intermediaries do to help data flow?
Data intermediaries are essentially collaboration mechanisms deliberately formed and structured to enhance the supply, flow, or use of data among specific partners—and to strengthen the relationships among various data stakeholders. Data intermediaries often work across multiple organizations, including government, the private sector, nonprofit organizations, academia, and even the media—and any of these organizations can contribute to it. Intermediaries can take on a range of tasks, including compiling, curating, and integrating data from various sources; validating the quality of data and identifying data gaps; facilitating stakeholder feedback, and building the data capacity of data providers and end users—all in the name of building trust between data providers and users.
Environmental data intermediaries are already playing pivotal roles in fixing data plumbing in a variety of areas, including air, water, and biodiversity. All are structured in different ways based on the needs of the particular data providers and users they serve. For example, OpenET is a nonprofit organization bringing together resources and skill sets from federal agencies (e.g., USDA, NASA and USGS) and the private sector to provide access to granular information on evaporation from vegetated landscapes for farmers, water managers, and other user groups.
They do so by making data from satellites more accessible, trusted, and scaled to the local level.
Many data intermediaries also curate and centralize information that would otherwise be hard to find and interpret for specific use cases. For example, the Fire and Smoke Map, a collaboration between EPA and the US Forest Service, leverages data from government and private sources in a map tailored to help the public limit their exposure to wildfire smoke. EPA worked to incorporate data from low cost sensors installed across communities to help meet the need for wide-spread information on smoke in near-real time—rather than just relying on its own network of monitoring stations.
Other data intermediaries like eBird have been successful in mobilizing a variety of resources—including financial and in-kind contributions such as networks of birdwatchers, to serve multiple use cases. These include everything from individual birders planning their next trip to siting large wind turbine projects where they will least impact specific species (like eagles). The intermediary has enabled data collection and use at a scale that would otherwise be impossible, and has helped build trust in alternative sources of data in the process.
What enables the success of a data intermediary?
From complex problems like modernizing environmental permitting to understanding the sources and quality of our drinking water, data intermediaries have only scratched the surface when it comes to meeting the many cross-agency and cross-sector needs we see around environmental data. But what enables them to succeed in the first place?
We conducted interviews with leaders involved in setting up data intermediaries to find out—and here’s what we learned:
Purpose: Intermediaries must communicate very clearly about their problem statement, potential solutions, and the purpose of the intermediary itself. Successful intermediaries are also savvy about regulatory processes and what they mean for their strategies around engagement, accuracy, etc.
People: Intermediaries need people who are externally focused and who regularly interface with partners and constituents to build and maintain trust. They must be sufficiently staffed to help leaders navigate operational silos, partnership dynamics, and organizational politics. Intermediaries also need to create teams across domains—both technical domains (e.g.,data science) and legal or policy domains—to maximize their impact on decision making processes.
Resources: Intermediaries must secure funding or in-kind resources to support the backbone of the collaboration—many mobilize government resources, especially to support underlying science (e.g., NSF).
Governance: Intermediaries do not take a one size fits all approach—they can be structured in any number of ways, within government or outside of government. Intermediaries must also navigate a set of complex issues around ethics, including issues like privacy, tribal sovereignty, racial bias, and other issues. Establishing clear norms and expectations helps reduce operational friction and protect the needs of data constituents.
While these are by no means the only factors underpinning the success of a data intermediary, they do offer a starting point for those eager to start fixing the data plumbing linked to their problem area—and hence to curate and deliver data that is just right for their particular use case. Organizations like GovLab have developed ample resources to help those in the private sector working to meet public data needs in creative ways.
More Plumbers Needed
We need more data intermediaries to channel and transform the flood of data we have into useful and stable flows that meet individual, organizational, and community needs. From understanding the quality of our drinking water to data-driven environmental permitting, we see nearly limitless opportunity for would-be data “plumbers” that are keen to bring organizations together to build trust and fill key data gaps. To help that happen, EPIC will continue working to distill lessons from ongoing efforts across data intermediaries—but for more on what we’ve learned to date, check out this overview.
Have ideas about where data intermediaries could be helpful or how to get one up and running? Don’t hesitate to reach out!