Sip Happens™ is a tongue-in-cheek, propaganda-style map created for International Straw Day that cheerfully celebrates convenience while quietly revealing its consequences. Built through iterative prompting, the map layers real-world microplastic data with sea turtle nesting sites, letting the horror emerge only as you zoom in. There are no straws on the map—just the conditions that make them lethal—because the point isn’t to shame a single object, but to highlight the systems that made it disposable in the first place. It’s bright, it’s playful, and if you linger long enough, it gets deeply uncomfortable. Just like progress. 🙂

See map here.

Created with Web Mapper GPT.
Datasets found using Perplexity Plus.

Original Prompt

I would like to create a tongue-in-cheek critical cartography map of plastic waste (in particular plastic straws) for International Straw Day.

Much of the world saw a viral video clip of a sea tortiouse with a straw stuck up its nose at some point.

I would like to design a sensationalist map that takes the piss out of the straw industry by highlighting:

– floating plastic waste in waterways
– sea turtle zones and habitat

The map can have these two types of datasets overlayed. It should highlight where the datasets overlap one another in particular.

I’m thinking the map can be in 1960s Americana style, sarcastically celebrating straw use and commercialism in marketing slogan type title while the map is actually showing how horrible plastic waste is and how it negatively impacts sea life (i.e,. turtles. The map should be a globe that the user can spin, if possible. Or Leaflet. Let’s mock up a color palette and title and subtitle and find two datasets that will work for this. Then we can create a schema and maybe a legend or some other elements, including perhaps an image of a dead turtles that are only visible when people zoom in far enough on the map or something.

Please come up with three creative, cynical, tongue-in-cheek sensationalist (but ironic) titles and visualization techniques to tell this story.

Below is a list of potential datasets we can use. When you come up with the narrative, titles, and visualizations, please make sure they can be built using 1-2 of these datasets. Thank you!