Carr et al had a similar idea - applied to color encoding - back in the 80s! (From www.jstor.org/stable/2289444, paywalled…)

Congrats Kaitlyn!!

🙏

Hi Lynn, curious if you’ve tried LLM based approaches (like LLooM: github.com/michelle123l...) and if so how they’ve fared for you

And congrats to you, too!

Hi, I’m a main author of the Vega/Altair curriculum notebooks. Indeed these focus on tool learning and aren’t intended as a standalone text for a full vis course. We combine it with many other papers, links, and lectures, as in courses.cs.washington.edu/courses/cse5...

FWIW it took UW IT about a month to complete our subdomain request, but once set up you can administer it yourself.

Updating DNS records for a top-level UW managed subdomain was painless, too. (We did it for @idl.uw.edu.) You just need to add an `_atproto` sub-subdomain, then add the TXT record to that.

Nice! I loved that work and always thought it would be good to do more like that 🤗

Congrats Sanjay!

Love this work! Also related is the Boba project, led by Yang Liu and @kalealex.bsky.social, which includes a variety of multiverse visualization and assessment methods. idl.uw.edu/papers/boba

1️⃣0️⃣0️⃣0️⃣ 🙏 📈

We could precompute the projection and the visualization would load a lot faster, but I wanted to keep all the spatial processing details in the example so folks can see how it’s done. Internally we’re working on a publishing tool that will optimize load times and precompute preaggregations, too!