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#DataViz

21 posts18 participants1 post today
Public
A. Nicholas

It's time for a #Measles dashboard update:

public.tableau.com/app/profile

The landing page now has a histogram AND a national map, capturing statewide totals. This is especially valuable since some states aren't including county data, or are including divisions like regions, which can't be captured on the cases-by-county map.

This project was constructed from local and state data first: I don't pull from CDC's national totals, but I do check my data against them frequently. Wherever local and state data aren't available, I use news articles. Every entry includes a source link in the cases-by-county table.

#PublicHealth#DataViz#Tableau
Public
Di

Here's my first contribution to the #30DayChartChallenge 2025. Horrifying statistics about misinformation! But also hot tips to cope!

Four in five of us (adults in Australia) reckon: "The spread of misinformation on social media needs to be addressed."

And that "People need to be taught how to identify misinformation."

So we're starting there! This is the SIFT method:

S: Stop. Don't read a post until you know where the info is coming from. And stop if you're overwhelmed.

I: Investigate the source. Maybe hover over their social media profile. See what Wikipedia says.

F: Find better coverage. Before sharing, check if other websites (reputable ones) say the same thing.

T: Trace claims, quotes, and media to the original context. Check the date. Try reverse image search to see where pics came from. Read full quotes, not just ragebait headlines.

97% of adults in Australia have limited skills to verify information online. 45% no ability. 52% emerging ability. 3% developing ability. Source: Sora Park, Tanya Notley, T. J. Thomson, Aimee Hourigan, Michael Dezuanni, 3 Dec 2024, https://apo.org.au/node/328959. Chart: @DiDoesDigital
Try the SIFT method: Stop. Investigate. Find better coverage. Trace claims, quotes and
media to the original context. Source: Mike Caulfield, https://hapgood.us/2019/06/19/sift-the-four-moves/. Adapted under CC BY 4.0: https://creativecommons.org/licenses/by/4.0/.
#DataViz#DataLiteracy#online
Public
ReDATA, University of Arizona

🦷💰 Did you know that untreated dental disease costs the U.S. $45 billion in lost productivity each year?📊 Explore more eye-opening stats in Stefan Marinic’s award-winning visualization from the undergraduate category of University of Arizona’s 2023 #DataVisualization Challenge! Check it out: doi.org/10.25422/azu.data.2272. Image: Marinic (2023). CC-BY 4.0.
#OpenData #OpenScience #DataViz #DentalHealth #UniversityofArizona

A visualization using statistics from the CDC to help identify startling facts and figures in hopes of creating more discussion in regards to the state of oral hygiene in America
Public
Tyler Morgan-Wall

Great 3D #RStats #dataviz of #gaming data (!) on DIB on the distribution of frags in the classic Counterstrike map, de_dust2. The author followed a tutorial by @mrpecners.bsky.social (not on mastodon) and commented that the hard part was getting the data--the 3D rendering was trivial!👍 Shows the power of a good tutorial and #rayrender!😀

reddit.com/r/dataisbeautiful/c

Orange and yellow 3D heatmap of frag locations in the counterstrike map de_dust2
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