We’re in a particular moment for environmental and climate data—it’s quite present in government agendas, civil society strategies, and even the public imagination of science and data as key components in our drive to tackle climate change. For instance, in the US, millions of dollars are being pumped into air monitoring through designations in the American Rescue Plan1 , resources are going toward opening up data related to climate; and more than ever, we’re seeing a focus on the role of communities in working with data to address environmental injustices and further prepare for adapting to climate change. But at times of relevant abundance (as we’ve seen in other sectors) where rapidity can outpace care, there is a heightened need to focus on the underpinnings of why and how we are approaching the strategies employed.

My earliest experiences working with environmental data were not with “data” as we define it, per se, but in working with data as a tactic in environmental justice advocacy. Working with communities and nonprofits in the “Cancer Alley” region of Louisiana lined with oil refining facilities adjacent to neighborhoods, we would conceptualize data as being socially situated—how data could tell the story of people—by collecting it from the grounds of a church or school rather than a point as close as possible to the fenceline of the refining facility. The data helped put experience and feeling into something concrete and depictive, allowing it to become an emotive narrative that could be widely shared and understood.

This was around fifteen years ago. This work coincided with a point of inflection for the Internet as well when social media and the networked projects of early waves of civic tech and open government were squarely inserting technology as a mediating device and community builder across all of our sectors, from social and environmental justice to media, government, and science. I spent over a decade with Public Lab2 focusing on the application of open tools and practices, from software and data to hardware, to support communities faced with environmental injustices by using data to tell the stories of their experiences. We focused on interrogating the top-down paradigms of how participatory forms of science were deployed, suggesting that openness could lead to better collaborations, accessibility (in tools and data available), and that people living with environmental injustices must have multiple places of input in environmental governance.

While we set the groundwork for a new wave of thinking in community science and data coupled with the incorporation of open tools and technology, the work of Public Lab started out in one of those moments of relative abundance. At that time, there was vast interest from government, academia, civil society, and philanthropy, and thus resources were provided that allowed for risk-taking and testing new methods in an attempt to push necessary transitions in science, media, government, and other sectors. But when the excitement began to slow, the cracks in these new methods that had been rapidly scaled and deployed showed.

As we matured and more groups and people began coming into the space, focused on building environmental monitoring methods and tools, my own interests started to shift toward the complexities that our work had either inadvertently created in the process of disrupting a space or that had been continuously overlooked. There was much that needed to be done so that the formal systems of environmental governance would open up and become more responsive to the strategies, tools, types of data, and people that needed to be involved and that were becoming more present as the availability of environmental monitoring increased.

My current thesis is based on these major questions: How do we break down the silos that currently exist between different sectors so that we can start to think differently about the data we have at hand? How do we better put that data to use? How do we think about the data, information, and local and historical experiences that communities have? I started mulling over these questions during the Trump Administration in the US, a time when environmental rollbacks were the norm, polluting industries were given new fire, and communities bearing the burden of pollution and the brunt of the climate crisis were once again positioned as the enemy. It was the exact opposite of the moments of abundance previously experienced, but perhaps a solid place to start since the political challenges were greatly amplified.

And yet, here we are again in a moment of relative abundance, where political agendas are focused on addressing climate and environmental pollution, centering justice, and calling for agency-wide rollouts of programs (how they are or are not meeting goals is a different article) as well as community-oriented and inclusive policy and philanthropy. Philanthropy is rising to the occasion to move more funds into the climate space, and we’re seeing more people than ever engaged and activated to find solutions to address our reliance on dirty energy and, well . . . basically save the planet before it becomes completely inhospitable.

In this moment of relative abundance, our collective goal should be focusing on a cohesive and holistic environmental and climate data landscape that is truly representative of how communities experience living in a place. We must establish a data landscape that is responsive to the broader national and international agendas that intend to lead us toward cleaner energy futures while doing so in a just manner. In our current climate, data should not be thought of as the end goal, but as an exclamation mark that puts emphasis on what we are seeing, feeling, and experiencing as it relates to climate change and environmental pollution. Data can help us make the experience being lived become something that can be examined and litigated; it can point to nuances in experience between communities living miles apart from each other. Data can tell both the contemporary and historical constructions of how environmental pollution has been unequally distributed worldwide. It can also be the backing for our solutions, the string that connects communities working on similar issues, and the last puzzle piece leading to environmental remediation. So while data (and any other technologies) are not the promised silver bullet, environmental data will be a key piece of the tool set to shift the way people and places connect.

As we rise to this abundant moment, there are two key angles to work from that respond to a multidirectional data movement: data accessibility and usability and the power of community-collected and -governed data. I’m especially interested in interrogating these areas and how they are being approached as the data space becomes interested in environment and climate and the environmental and climate justice and advocacy space starts to think more about data. At the same time, the US government (as well as others) is looking at the environmental role of data in addressing agency directives, such as through the Justice40 initiative.3 To see movement and maturity in connecting people, projects, and agendas, our directives should include working together on: 1) ensuring the data we do have available is accessible and able to be found and used; and 2) identifying where community data and information are most usable, as well as the places where collective management and governance can be modeled.

Accessible and Usable Environmental and Climate Data

There are technical specifications, standards, communities of practice, and methods (e.g., RDA⁴, FAIR⁵, CARE⁶) to reference for approaching data accessibility, but this part of the article focuses on several underpinnings that are often overlooked when ensuring that environmental and climate data are both accessible and usable.

To start, “open” does not assume accessibility or usability. While there are efforts underway to focus on opening environmental and climate data sets, open data has never automatically been accessible; at times, openness has even been used as a ploy to respond to open data requirements while ensuring that the data cannot actually be used. Broadly, open data requirements should be coupled with accessibility standards (found in the above mentioned standards and practices, such as FAIR and CARE) that ensure usability both for the core intended purposes and beyond original intent.⁷

If we are to meet this moment of resounding urgency for addressing climate change and environmental injustices, data use for purposes other than that which was originally intended should be a central consideration beyond primary research. When environmental data is collected, it almost always is in response to a proposed research question that then determines the collection methodology and use. However, the data we collect would have significantly more meaning if accessibility and usability were considered in tandem with research methodology, collection, and management practices. A core goal of our collective efforts in climate and environmental research should be to ensure that other scientists, social scientists, public health researchers, community researchers, and others have access to data to ask new and/or different questions and build their own solutions (see Open Environmental Data Project’s opportunity brief on data Beyond Original Intent⁷ for examples of possible environmental action through accessible and usable data).

Underscoring the ability to think about and use data in different ways, ensuring that data are accessible and usable can likewise lead to new and different stories about climate and environmental experience. Data as part of the knowledge commons can be translated from different perspectives, especially those that are often overlooked, and lead to new research questions and solutions that would have been impossible to discover if data were separated from people and places. To ensure we are able to do this, concentrated attention should be placed on the full data lifecycle—asking ourselves what the life and afterlife of environmental and climate data look like. Too often, we rely on antiquated institutional arrangements (e.g., data sharing agreements) that deny ownership, control, management, and accessibility rights to people that should have the explicit ability to use data. As a community of people interested in environmental and climate data, part of our responsibility to ensure accessibility and usability must be to model and attempt different methods for governing shared data resources.

As the above indicates, we have spent a significant amount of time and resources considering the technical infrastructure of environmental and climate data, but for data to be usable, the social infrastructure that puts data to work must receive equal consideration. Technical data systems are presently receiving the focus, especially as technological advancement vastly outpaces the infrastructure in which data lives, related to environmental decision-making and governance. While it is important to rethink our digital infrastructure and prioritize updates and system modernization, on the other end of the scale, there should also be a plan to overhaul outdated systems so that: 1) they speak to the current tools and technologies that we have today; 2) metadata and stories can sit easily alongside other environmental data sets; and 3) researchers have a wealth of data available to ask new questions as described above. Hand in hand with our technical interventions, the social infrastructure and context for data requires equal, if not greater, consideration. Updating the design of work processes and practices, training programs, higher education programs that funnel people into enforcement and compliance positions, and knowledge transfers between agency staff (closer to communities) and directors (institutional culture holders) is required to create a workforce that can effectively engage with the complexities of data accessibility and use. We should be focusing on how people think about the data sets they work with and maintain; how they center the people that will be impacted by the decisions they make with data; how they ensure the goals of justice and equity will be met through their daily practices; and how they connect with other people to find, understand, contextualize, and share data.

Finally, across all considerations, one key and important element is desiloing the space of environmental data, creating well-governed, usable, and productive spaces for people from different sectors to address the above considerations collaboratively. Without this, we continue to risk the creation of redundancies, duplications, and an environmental future stymied by the lack of ability to coordinate and collaborate.

Much of what Open Environmental Data Project⁸ works on is examining these accessibility structures (or lack thereof) through our collaborative projects, such as Beyond Compliance,⁹ a forthcoming Data Facilitators Consortium,¹⁰ Open Climate,¹¹ and generally ensuring that there are spaces and opportunities for people to coordinate and work on structural issues within the environmental and climate data space. As a community of environmental data practitioners, we aim to ensure that instead of primarily building programs around singular data sets, the lessons and language of data can be broadly usable and accessible through institutionalized curricula, workshops, and training that pass the baton of “capacity building” from community to include the government and others. Such a structure is necessary to ensure that we can cohesively work toward a better environmental data ecosystem.

The Power of Community Data

There is also significant power in the implementation and use of community environmental data and the tools that we use to collect data. The role of community data in the environmental governance landscape is vast and can range from community education to enforcement (though far rarer)¹² but should be thought of as one piece of the puzzle. Community data can get the process of further investigation or management rolling, as it tells the story of a place from the most intimate of vantage points: that of the people living in it.

Communities are not monoliths. The interests and priorities of the people that make up a community will naturally differ, especially where environmental resources or personal livelihood are concerned. But there is accountability in being part of a community—links that share and bind us to one another, whether through place, experience, or other identifiers. While data governance and stewardship models have proliferated in other spaces (for instance, see Connected by Data, Aapti Institute, and GovLab), they are relatively underexplored in environmental and climate data. Designing environmental stewardship models for how we collectively make decisions about with whom, where, and how we share our data is necessary. Data is a basic tool of environmental governance. Researchers, enforcement, and compliance officers need access to data to do their jobs. For communities faced with environmental injustices, a key part of the unfortunate burden they bear is demonstrating potential harm, and data is one such tool to do so. But environmental data can also be used to cause harm, both intended and unintended. Because of the far-reaching impacts of environmental data, stewardship and governance models should be prioritized for the space in which it will function (see emerging work from OEDP on Community Data Hubs and the Internet of Water).

The role of local experience and knowledge has gained traction as it has been able to provide context and meaning for environmental data sets (e.g., indigenous knowledge in U.S. federal policy decisions¹³). The use of strategies such as journaling, documentation (i.e., people saving news stories over the course of a decade about a polluting facility), logging the sensory effects of pollution (i.e., odor logs), oral histories, and photographic depictions all tell the story of the people of a place in ways that data, as we commonly think about it, alone cannot. Moreso, data and information shared by communities can constructively provide new ways of thinking about an environmental situation; it can place emphasis and meaning on places and objects that are culturally important or sensitive (e.g., Forensic Architecture’s work¹³ on burial sites, environmental racism, and pollution in Louisiana). It can also connect the vast histories and discrepancies across the world through experiences previously untold or not shared because of colonialism, neoliberalism, and the overshadowing politics of the entrenchment of industry and government. While environmental governance and decision-making have room for input, such as in the US processes of responding to RFIs from federal agencies (e.g., OMB’s RFI¹⁴ on advancing equity and OSTP’s RFI¹⁵ on equitable data engagement and accountability) and in public comment periods, these are still obscure processes that restrict input from a great number of people in the general population. As part of the work being done, the implementation of places for community input through different formats of information sharing should be diversified.

Various iterations—such as citizen, community, and participatory science—have had a place in environmental decision-making at agencies such as the Environmental Protection Agency. But participatory science (as is the au courant phrase) has largely been seen as an outreach strategy, a way for the public to interact in federal programs rather than a genuine tactic for providing and receiving rich, nuanced data and information that can lead to better environmental governance. The language of “filling data gaps” has a complicated history because of its perception as a minimizing framework, but if we equate “filling data gaps” to providing local, contextual, and bounded-in-community data that can work in tandem with large data sets and/or with government monitoring programs, there is extensive value. While capacity issues persist in both government and communities and the same concerns exist over creating spaces where we can collaboratively work on what these conjoined data ecosystems look like, the heightened interest in justice and equity clearly points to this as a prime moment to focus on challenging these barriers.

In tandem with the rise of community data, there has also been a suite of tools designed to make the monitoring landscape more accessible, including open software, open science hardware, and other forms of low-cost tools (categorically different from open tools because of their proprietary nature). The role of community data would be greatly enhanced with further investment in open tools to conduct environmental monitoring for a number of reasons, but one to highlight here is that tools like open science hardware can shift the way we understand data through processes such as critical making,¹⁶ where we learn as we use tools, fix them, build new versions, and collect and analyze the resulting data.

This leads to the final point on community data in the environmental and climate context. As more communities start to experience the effects of climate change, and as environmental justice enters the mainstream dialogue, community data in all its forms can become a powerful tool for community building. Environmental and climate data can provide a central source—whether indicating a negative health trend or pointing to a place where a wetlands restoration project is working—for people to gather around. By making accessible tools that surround data and science, we can further equip people with new ways to engage in decisions about their environments rather than relegating people to acting as mere bystanders. Instilling data as a tool for community building, management, and better governance of shared resources can work toward creating a more community-centered future for all our environments.

In this drive toward a clearer and more participatory manner of data use in the environment and climate space, there are challenges: lack of trust between sectors; problems with siloed spaces that are reductive to our environmental, climate, and justice goals; lack of cohesion between agency staff working with communities and staff tasked with implementing agency policies; resource distribution that promotes competition rather than collaboration in providing solutions for the climate crisis; and the time and resource intensity of community monitoring. The list is long, but these challenges are not insurmountable during a period of relative abundance, rapid urgency (needed to address climate change and pollution), and a matured digital landscape that has given us numerous tools for collaboration. If we want to shape a future for addressing environmental pollution and climate change, data must be a part of it, and all the people involved in creating, maintaining, and using that data—from scientists to concerned communities—must have a place in doing so. Environmental data alone will not shift and change the world, but the ways in which we put data to work for us and implement data in thinking cohesively about who is part of our environmental decisions can lead us to places where a more collaborative, productive environmental future is possible.

Bio:

Shannon Dosemagen (she/her) directs the Open Environmental Data Project (OEDP). OEDP focuses on building spaces to grow the global conversation on environmental and climate data access and use. Previously, she co-founded Public Lab, a community that uses open approaches to support people in asking and answering environmental questions, and served as its executive director for a decade (2010-20). Dosemagen is also a co-founder of the Gathering for Open Science Hardware and a collaborator in the Open Climate community. For her work, she has been awarded fellowships with the Shuttleworth and Claneil Foundations, the Harvard University Berkman Klein Center for Internet and Society. She currently serves on the boards of Code for Science and Society, the Open Science Hardware Foundation, and the (US) National Parks Conservation Association. Previously, she chaired the National Advisory Council on Environmental Policy and Technology (NACEPT) as well as the Citizen Science Association.

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