Ok, so that guy complained tonight (?) about the state of things when he came back into office?
Um...this is one of many things he left behind from his last time in office.
In January of 2021, I created this piece to help myself process what was happening. I started when there were only 400,000 American deaths from Covid. I updated it when we hit 500k. And I just couldn't update it again.
The #plushtodon are fluent in English of course, as is @destatis For an international audience this #datavis of the latest population projection for Germany can be linked to English independently of browser localisation. Also – unlike the #plushies – use your opposable thumbs right away on your smartphone. The age pyramid now has feature parity at all sizes.
https://service.destatis.de/bevoelkerungspyramide/#!l=en
New paper ✨
»Conceptual Analogues: Coming to Terms with Data Visualisation«
https://doi.org/10.11588/ic.2025.1.113533
In which I propose conceptual analogues as terms that fuse theory and practice to expand the language of data visualization. It is based on a contribution to the early-pandemic workshop »What is the Digital Doing?« and is out now in a special issue of Interface Critique, edited by Nina Tolksdorf and Lindsey Drury.
#DataVis #Critique #Theory #CriticalDataVis #DigitalHumanities #InterfaceDesign
Kleines random Update, wenn man mal wissen mag wie sich die Aufmerksamkeit für #talkshows (#lanz und co) so auf Plattformen wie Bluesky & Mastodon verhält, ich hab die letzten paar Monat mal visualisiert.
Ist jetzt noch nicht so richtig fertig aber wer mal in der #datavis herumstochern mag: feel free.
https://observablehq.com/@arrrrrmin/attention-is-all-you-need-for-talkshows
RE: https://hachyderm.io/@dubroy/115631863574134307
nested glyphs on a temporal citation chart and they even got it right in black and white. very nice!
reminds me of Citeology by folks at Autodesk: https://www.research.autodesk.com/publications/citeology-visualizing-paper-genealogy/
oh shit, the stats found out about the data... the'll never get me, i'm always two itetations ahead! #datavis #thuglife
Raj's dashboard, updated this morning, shows Stratus dynasty with diversified XFG.3 family at plurality, accounting for quarter of all samples. Notably, GISAID submissions don't reflect CDC's estimated growth of XFZ & XFV recombinants.
GISAID data for the most recent four-week period is dominated by paltry submissions from New York (80 sequences), followed by Maryland (45), Colorado (41), Minnesota (33), and Illinois (26).
After missing last month's update for reason of government shutdown, #CDC's most recent dataset, updated Friday, finally breaks out estimates for multiple XFG subvariants.
Nowcast suggests three XFG strains have gained significant share in past four weeks, along with two recombinants, XFZ (child of PG.3.2 and XFC.3) and XFV (child of LP.8.1 and XFG.3.3.1).
Note that, in absence of robust data from states, CDC has given up modeling historical estimates, instead giving only shares of reported sequences.
❖ #ThisIsOurPolio #variants #CovidIsNotOver #dataviz #datavis
![Chart: Estimated and Reported U.S. Variant Proportions by Common Name
Sources: CDC, Cov-Lineages, NYITCOM, D. Focosi, WHN, others
[ beadsland on Ko-fi ]
Reskin of CDC's Variants Nowcast, and any significant variants in GISAID not broken out by CDC.
Four bar-style tree-charts, for four-week periods through Oct 26–Nov 22. Legend of last four-week period, organized by subheadings of color-grouped families and convergent clusters. Percentages overlay each color key, reflecting share as of most recent tree-chart.
Nearly all WHO-Vaccine-Target JN.1 dynasty. Stratus XFG family accounts for over four fifths share.
For 10/26–11/22, packed bubble charts fill single-variant tiles, indicating diversification (per GISAID) not apparent from CDC's Nowcast.
Legend:
XFG [reds]:
69% - XFG.2†, XFG.3†, XFG.3.4.1 / QF†, XFG.4.1† & other Stratus XFG
10% - XFG.14.1
8% - XFG.6, XFG.1.1† & other XFG.1
JN.1.11 [browns]:
9% - XFZ, XFV, NW.1 & FDA-Vaccine-Target LP.8.1
0% - other JN.1.11
JN.1 + FLiRT-LF-7 [blues]:
⅛% - LF.7.9
¼% - other LF.7
LF.7 + NTD-meets-RBD [purples]:
⅕% - XFC
0% - other LF.7 + NTD-meets-RBD
WHO-Vaccine-Target JN.1 [green]:
0% - XEC
Other [greys]:
4% - Nimbus NB.1.8.1 / PQ, XFY & XDV.1
⅓% - Other (not specified)
_____
XFC is a child of April's WHO-Vaccine-Target scion LF.7 and Mayish JN.1.11 scion LP.8.1.1 / NY.
XFZ is a child of left-field WHO-Vaccine-Target scion PG.3.2 and Augustish recombinant kid XFC.3.
[Some footnotes omitted, due to too many recombinants.]](https://files.mastodon.social/cache/media_attachments/files/115/605/018/146/501/021/original/0fd9eb687def5fa0.jpg)
After missing last month's update for reason of government shutdown, #CDC's most recent dataset, updated Friday, finally breaks out estimates for multiple XFG subvariants.
Nowcast suggests three XFG strains have gained significant share in past four weeks, along with two recombinants, XFZ (child of PG.3.2 and XFC.3) and XFV (child of LP.8.1 and XFG.3.3.1).
Note that, in absence of robust data from states, CDC has given up modeling historical estimates, instead giving only shares of reported sequences.
Raj's dashboard, updated two weeks ago, shows Stratus wildly diversified, having spawned multiple third-generation pango aliases & descendant recombinants. Previous data had suggested XFG was stagnant.
GISAID data for the latter two-weeks-and-change of the most recent period is dominated by submissions from California (120 sequences), followed by New York (87), Minnesota (49), and Colorado (36)—paltry all round.
❖ #ThisIsOurPolio #variants #CovidIsNotOver #dataviz #datavis
![Chart: Est. & Reported U.S. Variant Proportions by Common Name
Sources: CDC, Cov-Lineages, NYITCOM, D. Focosi, WHN, others
[ beadsland on Ko-fi ]
Reskin of CDC's Variants Nowcast, and any significant variants in GISAID not broken out by CDC.
Four bar-style tree-charts, for four-week periods through Oct 26–Nov 22. Legend of last four-week period, organized by subheadings of color-grouped families and convergent clusters. Percentages overlay each color key, reflecting share as of most recent tree-chart.
Nearly all WHO-Vaccine-Target JN.1 dynasty. Stratus XFG family accounts for over four fifths share.
For 9/28–10/25, packed bubble charts fill single-variant tiles, reflecting GISAID detail not shown by CDC's Nowcast.
Legend:
XFG [reds]:
69% - XFG.2†, XFG.3†, XFG.3.4.1 / QF†, XFG.5.1†, XFG.4.1†, XFG.5.2†, XFG.3.4.3 / QS† & other Stratus XFG
10% - XFG.14.1
8% - XFG.1 & XFG.6
JN.1.11 [browns]:
9% - XFZ, XFV, NW.1 & FDA-Vaccine-Target LP.8.1
0% - other JN.1.11
JN.1 + FLiRT-LF-7 [blues]:
⅛% - LF.7.9
¼% - other LF.7
LF.7 + NTD-meets-RBD [purples]:
⅕% - XFC
0% - other LF.7 + NTD-meets-RBD
WHO-Vaccine-Target JN.1 [green]:
0% - XEC
Other [greys]:
4% - Nimbus NB.1.8.1 / PQ, XFY & XDV.1
⅓% - Other (not specified)
_____
XFC is a child of April's WHO-Vaccine-Target scion LF.7 and Mayish JN.1.11 scion LP.8.1.1 / NY.
XFZ is a child of left-field WHO-Vaccine-Target scion PG.3.2 and Augustish recombinant kid XFC.3.
[Some footnotes omitted, due to too many recombinants.]](https://files.mastodon.social/cache/media_attachments/files/115/593/606/530/127/283/original/2d2928fcb1c3ff88.jpg)
RE: https://vis.social/@InfoPlusConf/115588044309671590
wow!! so fast! thank you, @InfoPlusConf, for putting the #infoplus2025 talks and discussions online and making them freely available. really appreciated! sad i couldn't be there in person.
A need some fresh pair of eyes:
✅ Is this viz clear?
✅ What does it show?
✅ Would you change anything?
My curve text tecnique is still quite crappy but dont know how to do it better at the moment, please disregard that!
#data #dataviz #datavisualization #datavis
#run #running #runnersofmastodon
Fellow, Upshot at New York Times, New York: https://job-boards.greenhouse.io/thenewyorktimes/jobs/4618265005?brid=O6xLmquKZfEwkWIP2onbsg
⏰ tomorrow, Nov 19, 5pm Berlin/4pm London
“Data Vis for Cancer Patient Education“ - a #DataVis #DataViz #BioVis #STEM talk
Link & Abstract: alt-text and also:
biovis.net/2025/meetup/ (right under picture)
🌌 “Our Energy Nexus” is featured in #InfoPlus2025!
This interactive installation by Chloe Prock & friends reimagines energy as a collective force, turning pollution data into shared hope + action.
https://informationplusconference.com/2025/exhibition_items/02_item/
#datavis #dataart
Here's a new article on my Tutor/Mentor blog that may be of interest to #dataviz & #datavis networks. tutormentor.blogspot.com/2025/11/enga... In it I point to an "Interactive Research Map" created by a team at the University of Central America in El Salvador.
Raj's dashboard, updated today, shows Stratus wildly diversified, having spawned multiple third-generation pango aliases & descendant recombinants (incl much of Other on this chart). Previous data had suggested XFG was stagnant.
GISAID data for the latter two-weeks-and-change of the most recent period is dominated by submissions from California (120 sequences), followed by New York (87), Minnesota (49), and Colorado (36)—paltry all round.
Despite profound diversification of XFG, CDC had yet to break out estimates for any of its subvariants.
#CDC's most recent dataset, updated Sept 26, showed Stratus XFG family dominating, with Nimbus NB.1.8.1 / PQ in second place, down to one-fourteenth share, this nearly neck-in-neck with FDA Vaccine Target LP.8.1 at one-seventeenth share.
Note that, in absence of robust data from states, CDC has given up modeling historical estimates, instead giving only shares of reported sequences.
❖ #ThisIsOurPolio #variants #CovidIsNotOver #dataviz #datavis
![Chart: Est. & Reported U.S. Variant Proportions by Common Name
Sources: CDC, Cov-Lineages, NYITCOM, others
[ beadsland on Ko-fi ]
Reskin of CDC's Variants Nowcast, and any significant variants in GISAID not broken out by CDC.
Four bar-style tree-charts, for four-week periods through 9/28–10/25. Legend of last four-week period, organized by subheadings of color-grouped families and convergent clusters. Percentages overlay each color key, reflecting share as of most recent tree-chart.
Stratus XFG family accounts for over three quarters share.
For 9/28–10/25, leading GISAID sequences make up for outdated CDC Nowcast. Packed bubble charts fill single-variant tiles.
Legend:
LF.7 + NTD-meets-RBD [red]:
77% - XFG.2†, XFG.3†, XFG.14.1†, XFG.3.4.1 / QF†, XFG.5.1†, XFG.4.1†, XFG.5.2†, XFG.3.4.3 / QS† & other Stratus XFG
JN.1.11 [browns]:
2% - FDA-Vaccine-Target LP.8.1
1% - KP.3
½% - other JN.1.11
LF.7 + NTD-meets-RBD [purples]:
½% - XFC
¾% - other LF.7 + NTD-meets-RBD
JN.1 + FLiRT-LF-7 [blues]:
0% - LF.7.9
1% - other LF.7
JN.1 [greens]:
0% - JN.1.16.1 / LF
0% - other WHO-Vaccine-Target JN.1
Other [greys]:
8% - Nimbus NB.1.8.1 / PQ
10% - Other (not tallied)
_____
Stratus XFG is a child of April's WHO-Vaccine-Target scion LF.7 and Juneish JN.1.11 scion LP.8.1.2 / NW.
XFC is a child of April's WHO-Vaccine-Target scion LF.7 and Mayish JN.1.11 scion LP.8.1.1 / NY.
† Variants, not broken out by CDC, that represent significant share of recent GISAID sequences.](https://files.mastodon.social/cache/media_attachments/files/115/523/131/493/453/391/original/0b53c82d056e6dda.jpg)
#Annoplot #dataviz development has been temporarily suspended as of October, after only about fifty lines added since last round of work in September:
https://hcommons.social/@beadsland/115295487903892225
Work in first week of October focused on:
* support for #datavis of partial periods of GISAID data
* tweaks to scrim and suds implementations
* revisions to captions to reflect current events
Work in first week of November focused on development of Buoy, a tool for floating self-boosted posts periodically, as a function of other posting behavior:
https://hcommons.social/@beadsland/115522549953210771
This added about 400 lines, plus another 50 lines to duplicate existing hotmods library:
![Chart: Annoplot Dataviz Library*: Project Profile
Subtitle: 12.8K lines† across component modules and significant submodules.
Multi-level pie chart organized into six major categories by color. Each outer wedge shows a tally of number of lines for that sub-component.
Brown buoy wedge notably exploded out; all others show no discernible activity.
A legend is split across both sides of the chart. Each key mirrors one of the wedges on the dual pie chart, along with a sentence or two description of each (sub)component thereby represented.
Caption:
* Pre-release development version 2025-11-09.
† Python, Markdown, C, Elixir, and shell source files. Blank lines omitted form tallies.
Exploded wedges reflect proportions of lines changed in prior 41 days. Dotted areas represent non-blank comment lines and Markdown.
Wedges:
🔴 levels
🧀 [blank wedge] - 460, 🧀 hospitals - 282
🟣 chirp
🧀 [blank] - 537
🔵 annoplot
🧀 [blank] - 544, 🧀 artists - 750, 🧀 artists/adorn - 360, 🧀 artists/deco - 511, 🧀 artists/legend - 419, 🧀 coord - 583, 🧀 coord/base - 259, 🧀 margin - 256, 🧀 util - 537
🟢 tiop
🧀 [blank] - 235, 🧀 bullseye - 321, 🧀 capacity - 455, 🧀 devpie - 572, 🧀 devpie/slice - 295, 🧀 variants - 770, 🧀 variants/legend - 389, 🧀 variants/orchard - 432, 🧀 variants/rajdash - 602, 🧀 variants/tree - 437, 🧀 …/tree/branch - 359
🟤 bots
🧀 [blank] - 181, 🧀 buoy - 437, 🧀 talky - 821
⚫ . [period by itself]
🧀 [blank] - 458, 🧀 TODO.md - 504](https://files.mastodon.social/cache/media_attachments/files/115/523/105/368/410/891/original/a6d5f966cf582207.jpg)
If you're following the #UNL #statistics` saga (proposed for elimination based on bad stats), you might find the seminar we gave yesterday interesting...
https://www.youtube.com/watch?v=fUk2R0UYWpA
It was weird to rail against someone for an hour, but strangely cathartic, and the #datavis seems to have been effective?
All #academics should be aware of the absolute BS that administration can create with perfectly reasonable sounding #data, #stats, and #metrics
A student told me about the new Oklab color space, which fixes a problems with previous perceptual color spaces (like LAB).
Unfortunately, when I tried Oklab instead of LAB to make color bins for a datavis, the lightness dimension is much longer, which makes it hard to show a lot of bins.
