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Carlos Scheidegger

in 1996, gave us the task by data type taxonomy (with overview first etc), but when did the very prolific, yet slightly dated triad user–data–tasks become a thing in visualization? asking for a friend

I literally wrote that section of the paper 45 minutes ago. If you ask me what is the design of the study we used, I can tell you "yes, we showed all independent factors to each participant". But I cannot tell you if that's "within" or "between" or "across" or whatever-they-feel-like-calling-it-today

(Add another one to my growing suspicion that I have some weird form of dyslexia-spectrum thing) I can never remember if it's across-subjects or within-subjects or between-subjects. I know the _meaning_, but the word association never sticks to my head. Might as well keep that google tab open forever

I'm hacking on some JSX+React stuff my student wrote. I feel so modern.

Well, that's one more thing Kosara and I disagree about.

Standard datasets _are_ important. You literally don't want to be surprised by the dataset when you're trying to understand a technique.

Synthetic examples serve a similar purpose: you _know_ what's in them, so you can check that your technique is doing what you expect.

If you design a new technique and show it on a new dataset, readers can't separate one from the other.

Our paper "Using Animation to Alleviate Overdraw in Multiclass Scatterplot Matrices" will be presented at CHI 2018 on Thu 4/26 at 11am in Montréal!

Our approach uses a simple animation loop to alleviate overdraw in one of the hardest settings---multiclass SPLOMs.

It is work with our former undergrad student Helen Chen, myself, Alark Joshi, & Beste Yuksel at USF, Eric Ragan at Texas A&M, and Lane Harrison at WPI.

See a demo and more at

What do you all use for cross-browser testing? I'm getting sick of infinitely tweaking CSS for 50 different devices and browsers by hand

Thanks to our @Liberapay donors!

I'm now redistributing ~50% of donations to the core @Mastodon project, and ~25% back to Liberapay itself. The rest will help cover hosting costs for

Schedule a small recurring donation here:

setting up a dask cluster on ec2 must be trivial, he said to his grad student, before giving up after 90 minutes of failure

The feature from Observable that I'm most excited about is, by far, the fact that you can easily call functions from other notebooks.

Taught d3 scales today in my class. I'll reiterate my opinion that scales are _the_ fundamental idea behind good visualization code. Even more so than joins and selections