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Training module teaches root-cause analysis and accessible mapping for equity-focused water data
Summary
An online module led by DataMaid and workshop co-organizers covered root-cause analysis, mapping best practices (projections, color palettes, accessibility) and reproducible R workflows using CalEnviroScreen and SAFER data.
An online training session in a two-part series on analyzing data for racial equity focused on root-cause analysis and mapping methods for water-quality and equity questions.
Hannah, partner at DataMaid, and Anna, workshop co-presenter and organizer, led the session. Anna described the core technique as iterative questioning: “ask why a lot, at least 3 times, usually closer to 5 or 6 times,” and recommended bringing community partners into root-cause work so data are paired with lived experience.
Why it matters: Presenters said equity-focused analyses require more than code — they require attention to accessibility, documentation and community engagement. The…
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