Despite the growing number of climate and environmental crises affecting the places and bodies we inhabit, there are precious few ways for people to engage in environmental decisions that will affect their communities.
In response to climate and environmental injustice, communities around the globe have for decades engaged in their own scientific monitoring and have campaigned to have this information included in regulatory, legal, and legislative processes. However, “invited spaces” of participatory environmental governance (e.g., environmental impact assessments, strategic environmental assessments, and public inquiry mechanisms) vary wildly in their accessibility and efficacy, and often do not have entry points to incorporate community data. Likewise, data collected by regulatory agencies, academic researchers, or mandated industry requirements are decontextualized and, as a whole, do not adequately reflect local values and cultural knowledge that may be critically important to a policy or a regulatory change. This means that each community that collects data to share their experiences, to counter industry narratives, to demonstrate where environmental management is succeeding or failing, is required to navigate complex local, regional, and federal laws and policies within dense legal landscapes.
The result is that community-driven data projects and community efforts to provide context are tragically under used. The existing models (open government data platforms, public comment and complaint systems, and proprietary sensor networks, to name a few) that attempt to act as a bridge cannot speak to the complexities regarding openness of public data and the sensitivity of personal data.
OEDP believes in approaching these complexities with robust data governance that facilitates a multi-directional information flow between communities and government and supports better decision making, trust, and regulation. In 2020 we began this exploration through looking at the role of data guilds, trusts, and collaboratives in the environmental governance space. We then furthered this inquiry by building out the idea of generative environmental governance and the conceptualization of an Environmental Trend Platform. In 2021, we began to move these ideas into the co-design of a Community Data Hub, which would increase data usability for environmental governance in three ways: (i) by providing a place for communities to make collective decisions about their own data while also (ii) modeling data governance approaches for sharing between communities, and (iii) between communities and government. Our goal is to demonstrate how socially networked open data streams (i.e., integrating and sharing knowledge across different community hubs or inputs) can preserve local values while enabling timely, relevant, and trustworthy decision-making by community members and their representatives in government.
This model is designed around community needs, which are often dismissed in larger data infrastructures. The Community Data Hub design includes ways to encode epistemic innovations (i.e., new ways of generating scientific knowledge) in understanding environmental risk and knowledge, and tagging systems which test new socio-technical features around sensitivity and privacy. Community data hubs require new governance approaches because of the complexities of both public and private data management, and the immediate need for community-government and community-community interfaces that can represent community needs both accurately and deliberately.
Community Data Hubs will grapple with the ways that community information is shared to allow for community representation and authority in environmental governance. Thus, in addition to space for communities to share data they have collected, the design should also facilitate governance feedback loops, for example through a repository where lawmakers can directly input relevant data for reuse, and connect community information to policy making. Each Community Data Hub design will be an expression of a community need and our community partners will determine the types of data or information that will be housed. Examples of data needs include public and open sources of environmental data and private and civic sector sources of data; in each respective community, the Hub must be designed with these contextual data needs in consideration. Through design, questions of privacy and policy, usability and searchability will be addressed. Additionally, the prototype design could provide a resource library, co-maintained by OEDP and communities for interaction with government on how to pilot new solutions. This could include: data sharing agreement templates and examples, existing legislation that communities could adapt or advocate for adoption, and policy templates. Ultimately, creating a tool that manifests the needs of its users is essential to the operative design of a Community Data Hub.
Our goal is to co-create a prototype with a working group of community members, government data stewards, designers, and researchers. This working group will identify and focus on a specified subset of data to work with, e.g., community-based experiences of climate change broadly, or an environmentally specific pollutant or pollution hazard. We envision a process in which this working group will conduct a series of design workshops that prioritizes community ideas and incorporates public feedback. OEDP and the working group will then collaboratively articulate a design for the Community Data Hub prototype. This articulation will serve as the launching point for sessions with local community groups in order to create use case studies, and the final documentation package for the prototype. We aim to co-create a microsite for the Community Data Hub prototype that includes a core case study on its use and a series of two-to-three case studies that demonstrate its use for climate and environment issues. Ultimately, in terms of process and outcomes, different priorities could emerge dependent on what is most important to the community in partnership.
The audience of this design and process includes: community members collecting and using data and are experiencing pain points with reuse and understanding, scientists engaging with communities and their data, public government and agency staff that want to engage with local data, and community organizations that are interested in building networks within their region.