EDGI is partnered with a few universities research units/programs, Union of Concerned Scientists, and other research labs and climate organizations.
EDGI has a main website where all of their information is stored. Based on a Google search, there is also a social media account via Twitter.
EDGI has several projects such as “A People’s EPA”, “Data Together”, and “Federal Environmental Web Tracker”
“Federal Environmental Web Tracker”: a public dataset to changes of federal environmental websites under the Trump administration and beyond. This one especially peaked my interest because it is fairly simple to navigate and there is also a Google Sheets version that is downloadable I believe.
EDGI obtains its funding from several 501 c 3 organizations but primarily relies on volunteer work. They are also offered compensation and reimbursement for some of their work or operations. EDGI is fiscally sponsored by Multiplier, a 501 c 3 organization that supports projects that have a planet-saving impact.
EDGI formed in November 2016 to document and analyze changes to environmental governance that would transpire under the Trump Administration. EDGI subsequently became the preeminent 'watchdog group' for material on federal environmental data issues on government websites and a national leader in highlighting President Trump’s impacts such as declines in EPA enforcement.
EDGI has created many projects that demonstrate tracking of environmental governance changes, specifically in environmental data infrastructure. It mainly deals with federal datasets and does not have much information on its website about engaging smaller communities.
There are 50+ members of this organization from academic institutions, non-profit and grassroots organizations, and professionals from a broad spectrum of work and life backgrounds.
Sub-units of this organization include one for environmental data justice.
There are five major programs: 1) investigating and analyzing the inner workings of federal environmental policy, through interviewing of agency staff, as well as data and documentary collection and analysis, 2) monitoring changes to, and exploring standards for, web-based information about the environment, energy, and climate provided by the federal government, 3) developing new ways of making federal environmental data more accessible to the public, 4) imagining, conceptualizing, and moving toward Environmental Data Justice, and 5) prototyping new organizational structures and practices for distributed, collective, effective work rooted in justice.
"The Environmental Data & Governance Initiative (EDGI) documents, analyzes, and advocates for the federal provision of environmental data and governance, from policies and institutions, to public access to information, to environmental decision-making. They seek to improve environmental information stewardship, promote environmental democracy, health, and justice, and to better adapt these all to the digital age." (Environmental Data and Governance Initiative, About section)
“It is difficult to imagine any of these studies exerting as much of an impact on public discourse and policy as they did if they had not been closely connected to litigation, advocacy, and regulatory interest in addressing the emerging issue of environmental justice.” (6)
“EJ scholarship has uncovered environmental and health disparities based not only on race, class, and gender, but also on ethnicity, nationality, indigenous status, immigration and citizenship status, sexual orientation, age, and the intersections among these categories (Nyseth-Brehm & Pellow, 2014; Chakraborty, Collins, & Grineski, 2016; Gaard, 2018). Activists are increasingly appealing to these diverse axes of identity to mobilize broad-based organizing on environmental, healthcare, and immigration policies (Hestres & Nisbet, 2018).” (9)
“In Europe, EJ is often seen as an extension of protections for human rights, including rights of access to environmental information, participation in decision making, and access to the courts, which are enshrined in the United Nations Economic Convention for Europe’s1998 Aarhus Convention (Mason, 2010). In the global South, EJ issues are more often framed as matters of climate justice, participatory and sustainable development and conservation, indigenous and women’s rights, food and energy sovereignty, workplace safety and health, or the environmentalism of the poor (Carmin & Agyeman, 2011; Carruthers, 2008; Martinez-Alier, 2002; Reed & George, 2018; Walker, 2012).” (10)
“The goals of community-engaged scholarship are the generation, exchange and application of mutually beneficial and socially useful knowledge and practices developed through active partnerships between the academy and the community (Engagement Scholarship Consortium, 2018).” (11)
“A more inclusive scholarly process is crucial for strengthening marginalized groups’ rights to access and create knowledge that can help build their power to influence regulation, policy, and institutional practices. ES is scholarship “done with, rather than for or on, a community” (Furco, 2005, p. 10), and this is reason alone to prefer ES to other modes of inquiry into EJ.” (15)
“Ensuring that map making is a democratic process owned and controlled by community members requires that local people, not outside researchers, define the geographic or other boundaries over what counts as part of the “community.””(29)
“EJ research can also ground-truth existing regulatory data that is out-of-date or incomplete, especially emissions data that is reported by industry. In addition, ground-truthing can show how environmental standards for broad geographic areas can fail to protect EJ communities from pollution hot spots that exceed those standards.” (31)
“Data scientists can also use large data sets and algorithms to develop new measures of environmental and social inequities. For example, a team led by researchers at the University of Minnesota recently created a “pollution inequity” metric, which measures the difference between the environmental health damage caused and experienced by a group or individual...” (33)
“While real-time analysis of crowdsourced data can help track the immediate effects of environmental disasters, it may not be as useful for documenting long-term, cumulative toxic exposures typical of many EJ issues. … Much of that expertise is concentrated in corporate, government, and academic institutions, which may be unable or unwilling to collaborate with community-based EJ organizations. EJ researchers could play a valuable role in helping to foster big data literacy…” (33)
“EJ storytelling is a means of gathering testimonial evidence for research and organizing (Evans, 2002). Stories are a grassroots form of making meaning that is often more accessible and immediate in its impacts than academic research, building commitment to collective action (Newman, 2012). Storytelling lends itself to communicating complex causality in a form that can be more memorable than scientific data (Griffiths, 2007).” (34)
In the “Introduction” and “Foundations” sections, the author describes the utility of an “engaged scholarship” approach to academic environmental justice research and outlines several models for engaged scholarship. These models lie along the spectra of the apolitical to the political, and include different types of development, types of engagement, and types of expertise. The author argues in favor of an engaged scholarship approach to EJ as a way to root EJ research in actual EiJ problems and EJ needs. Note that the author defines EJ with the four dimensions of distributive justice, procedural justice, process justice, and restorative/corrective justice.
The sections II. METHODS and III. CHALLENGES AND RESPONSES detail methods and potential pitfalls in engaged scholarship with local communities. Methods can include: investment in easy-to-use and low cost technologies for citizen science uses (e.g., online mapping tools, low cost air quality monitoring devices), using storytelling methods for cultural research and to advance EJ goals, and adequately training and preparing researchers for community collaborations (see Hyde (2017) framework on pg. 38). Pitfalls can include: scholars assuming homogeneity in a community, tensions between community goals and academic goals (e.g., scholarly productivity vs. community education), and limitations imposed by academic IRBs for collaboration. The author provides several examples of community collaboration focus, with an apparent focus on citizen science/crowdsourced data collection efforts.