This question has come up a couple times during our recent Open Calls (notes here) on organizing and advocacy.
The folx at @LESBreathe, for example, are starting a community-led air quality monitoring project that will generate data on particulate matter in the Lower East Side of Manhattan. At first, they will collect baseline data on air quality before a major construction project begins.
How can you make air quality results mean something to community members so that they will feel encouraged to take action?
Thanks for sharing any strategies that you've used or have experienced yourself!
Also, this relates to another separate question: How do you turn results about environmental pollution into personal actions that people can take?
These questions seem closely linked---wondering what things you can do in response to environmental data once you know its significance.
In my experience, well-thought out data visualization is a huge benefit to making content digestible, approachable, and meaningful. EDF pulls in some great supporting arguments for how data visualizing can support EJ action.
1. Storymaps are one great visual tool to embed monitoring data into, see this example here on pollution in Detroit.
Data visualization and justice are the focus of this group's work, which could be a great ongoing collaborative space for those interested.
Sunrise Movement has focused on data visualization through their organizing and policy advocacy. Their Digital Director gave this answer to the question, "What is your design process around data visualization?"
"When I do data visualization at Sunrise, most of the work occurs before I even open my script. I spend time meeting with program leads, directors, and staff to get to the heart of what information they need from the data visualization. I start by working with key staff on what their programmatic goals are, then how they know when they have achieved them, then what data are available to us to measure success along the way. By the time I sit down to write my code I’ve done all the hard work. On the tech side of things, I’m lucky to have a powerful CRM that syncs to our data warehouse (Civis), and from there I can make dynamic dashboards in Periscope. My one-off visualizations and any kind of spatial mapping is done in Python with a slew of packages, including Seaborn, Plotly, and GeoPandas."
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Thanks for sharing your experience and these resources, @julia_e_masters, they're super helpful!
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