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Collaboratively Managed Data
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January 18, 2023

Emelia Williams

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To read the full Opportunity Brief, click here.

When we imagine how environmental data can be managed for more democratic and effective environmental decision making, we must conceptualize what collaboratively managed data looks like—how to design infrastructures that reflect the values of diverse data stewards. The FAIR principles offer data producers, owners, managers, and users collective guidelines for enabling data and infrastructures to speak to each other. The CARE Principles for Indigenous Data Use consider the social life of data from an indigenous perspective, and more broadly brings to light a concern that should resonate across all decision-driven data spaces: how do we ensure collective benefits, control, responsible use, and ethics as community data weaves an important layer of context and localization into data ecosystems? How can better environmental data stewardship and management lead to more democratic and effective environmental decisionmaking?

Health and/or socioeconomic data stewards have embraced data guilds, trusts, and collaboratives as ways for people to engage in community, shared agreements, and legally binding relationships that govern how their data is managed and accessed. But such collaborative structures are rarer in environment and climate data spaces due to an overwhelming complexity of laws governing the environment (in the United States and on an international scale) and the need for multi-directional input (i.e., from various governmental agencies, court systems, communities, industry, non-profit interest groups, and academia, all with varying degrees of power and influence). Histories of extractivism and appropriation throughout interactions between frontline communities and those collecting, using, or managing communities’ environmental data are well documented. Additionally, while successful partnerships have integrated Indigenous Traditional Ecological Knowledge (ITEK) into data systems, namely in ocean observation datasets, many have struggled to integrate cultural and ecological knowledge. Challenges also stem from disagreements over what is included and who owns information about the environment; can you actually “own” a dataset about water quality from a particular stream in a watershed?

To address these conceptual and material challenges, we’re exploring what collaborative data stewardship can look like in varying environmental contexts, in service of frontline communities.  

The open source community—with roots in collaboration, community, and attempts to connect shared social spaces with technological meaning—has given us strong models for creating common places for shared knowledge and practice. Several organizations and communities have begun developing ideas around community environmental data stewardship. In this work, it is critical to interrogate legal mechanisms that define these collaborative spaces, as well as to ask the harder-to-scope social questions of how, with whom, where, and when data is shared. Exciting examples of work in this area include:

We’re interested in connecting the dots between discussions of data stewardship, sovereignty, and collaboration, as well as in building zones for considering how and what data is shared with whom. To this end, we hope to facilitate the design of infrastructures for collaboratively managed data that apply FAIR, CARE, and open principles while also respecting the social and cultural life of data and promoting greater community utility.