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#datavis

3 posts2 participants0 posts today
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sport of sacred spherical cows

Another four hundred lines for #AnnoPlot #dataviz project since last round of work in March:

hcommons.social/@beadsland/114

Work in May/early June included:

• tweaks to this pie chart, chirp logging, annoplot legend classes and newspaper columns orphan control;

• tweaks to variants #datavis: tree constructor process, alt-text pruning internals, legend subclass, tree constructor methods, name collisions and recombinant lineage assignments, family groupings and legend headers, variant mocking, title overhang, tile embossing, growth calculation, and captions, all including significant refactoring;

• migration of bug to legend footer, and build out of prioritized legend footnotes for prominent lineages and recombinants, including recombinant chains, with calculation and approximation of historical peaks, and pruning for space constraints of both alt-text and footer proper.

Chart: Annoplot Dataviz Library*: Project Profile Subtitle: 11.3K 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. Green variants wedges all variously exploded out; also, less so, blue artists/legend wedges. 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 2025-06-05. † Python, Markdown, C, and Elixir source files. Blank lines omitted form tallies. Exploded wedges reflect proportions of lines changed in prior 30 days. Dotted areas represent non-blank comment lines and Markdown. Wedges: 🔴 levels 🧀 [blank wedge] - 460, 🧀 hospitals - 282 🟣 chirp 🧀 [blank] - 535 🔵 annoplot 🧀 [blank] - 549, 🧀 artists - 374, 🧀 artists/deco - 503, 🧀 artists/legend - 161, 🧀 …/legend/deco - 258, 🧀 artists/pie - 287, 🧀 artists/text - 326, 🧀 coord - 583, 🧀 coord/base - 259, 🧀 margin - 255, 🧀 util - 535 🟢 tiop 🧀 [blank] - 235, 🧀 bullseye - 321, 🧀 capacity - 455, 🧀 devpie - 673, 🧀 variants - 518, 🧀 variants/legend - 348, 🧀 variants/orchard - 421, 🧀 variants/rajdash - 168, 🧀 variants/rajdash/suds - 280,🧀 variants/tree - 417, 🧀 …/tree/branch - 352 🟤 bots 🧀 [blank] - 181, 🧀 talky - 75, 🧀 talky/talky - 746 ⚫ . [period by itself] 🧀 [blank] - 427, 🧀 TODO.md - 348
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Marian Dörk

“To visualize with care is to visualize with empathy: to make visible environmental harm, surface suppressed narratives, reveal shared experiences, and confront the structural biases that too often remain hidden.”

nightingaledvs.com/visualizing

by @damlacay @dario and Weidi Zhang - general chairs of this year’s VIS Arts Program @visap:

visap.net/2025/ (submissions due 20 June)

Nightingale · Visualizing as a Form of Collective Care, NightingaleCare is easy to recognize on a personal level, especially when it takes the form of small, attentive gestures woven into daily life.
#datavis#art#care
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sport of sacred spherical cows

Since March, LP.8.1 has been dominant. FDA designates same as vaccine target, on very week its share has plateaued.

Data collection continues to be low priority nationally—as exactly zero regions have enough data for CDC to plot.

No new variants broken out by #CDC, although the "razor blade throat" variant, NB.1.8.1, remains significant in GISAID.

Raj's dashboard was last updated yesterday.

❖ #ThisIsOurPolio #Covid #Covid19 #SARS2 #variants #CovidIsNotOver #CovidIsAirborne #dataviz #datavis

Chart: Est. 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. Five bar-style tree-charts, for fortnights through 5/11–5/24. Legend of last fortnight, organized by subheadings of color-grouped families and convergent clusters. Percentages overlay each color key, reflecting share as of most recent tree-chart. For 4/27–5/10, packed bubble charts fill single-variant tiles, reflecting GISAID detail not shown by CDC's Nowcast. Legend: JN.1.11 + FLiRT31 [purple]: 73% - LP.8.1.1 / NY† & other FDA-Vaccine-Target LP.8.1 JN.1 + FLiRT-LF [browns]: 10% - XFC 3% - LF.7.7.2 2% - XFG.2†, XFG†, LF.7.9† & other LF.7 1% - LF.7.7.1 & LF.7.2.1 / PC WHO-Vaccine-Target JN.1 [red]: 6% - XEC, LB.1.3.1 / NL, XEC.4, XEC.4.1† & XFJ† JN.1.11 [greens]: 3% - MC.10.1 & PA.1 ¾% - KP.3 & XEQ ⅞% - MC.1, MC.19 & other KP.3.1.1 / MC JN.1.11 + FLiRT31 [blue]: ¼% - XEK Other [greys]: 0% - Razor-Blade-Throat NB.1.8.1 / PQ† & other WHO-Vaccine-Target JN.1 0% - Other (not specified) _____ XEC is a child of FLiRT cluster KS.1.1 and FLuQE cluster KP.3.3. XEK is a child of FLiRT31 cluster KP.2.3 and recombinant XEC. XEQ is a child of FLiRT cluster KS.1.1.2 and FLuQE cluster KP.3. XFC is a child of FLiRT31 cluster LP.8.1.1 and JN.1.16.1 scion LF.7. XFG is a child of FLiRT31 cluster LP.8.1.2 and JN.1.16.1 scion LF.7. [Add'l footnotes omitted.]
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Ele Willoughby, PhD

Happy birthday to founder of modern nursing, social reformer, statistician, data visualization innovator and writer Florence Nightingale (1820 – 1910)!⁠
Nightingale earned the nickname “The Lady with the Lamp” during the Crimean War, from a phrase used by The Times, describing her as a “ministering angel” making her solitary rounds of the hospital at night with “a little lamp in her hand”. 🧵
⁠
#linocut #printmaking #sciart #womenInSTEM #datavis #nursing #statistics #mathart #histsci #mastoArt

My linocut portrait of Florence Nightingale in blue with her oil lamp in gold with orange flame with her rose diagram of mortality for 1855 and 1856 clearly showing that lack of hygiene was the biggest killer of those injured in the Crimean War
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sport of sacred spherical cows

Updated #CDC estimates show we'd pretty much been in a JN.1.11 soup since Dec, until late March, when LP.8.1 took majority.

Data collection continues to be low priority nationally—as exactly zero regions have enough data for CDC to plot.

CDC breaks out recombinant XFC from FLiRT parent LF.7 . (Our dataviz now identifies parentage for each recombinant.) Raj's dashboard was last updated today.

❖ #ThisIsOurPolio #Covid #Covid19 #SARS2 #variants #CovidIsNotOver #CovidIsAirborne #dataviz #datavis

Chart: Estimated 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. Five bar-style tree-charts, for fortnights through 4/27–5/10. Legend of last fortnight, organized by subheadings of color-grouped families and convergent clusters. Percentages overlay each color key, reflecting share as of most recent tree-chart. LP.8.1 accounts for over two thirds. For 4/13–4/26, packed bubble charts fill single-variant tiles, reflecting GISAID detail not shown by CDC's Nowcast. Legend: JN.1.11 + FLiRT31 [purple]: 70% - LP.8.1.1 / NY†, LP.8.1.8† & other LP.8.1 JN.1 + FLiRT-LF [browns]: 9% - XFC 3% - LF.7.7.2 2% - XFG† & other LF.7 2% - LF.7.7.1 & LF.7.2.1 / PC JN.1 + FLiRT [reds]: 2% - LB.1.3.1 / NL 1% - XEC.4 ½% - XEQ 6% - other XEC JN.1.11 [greens]: 3% - MC.10.1 & PA.1 ⅓% - KP.3 2% - MC.1, MC.19 & other KP.3.1.1 / MC JN.1.11 + FLiRT31 [blue]: ⅓% - XEK Other [greys]: ⅐% - NB.1.8.1†, JN.1.16 & other WHO-Vaccine-Target JN.1 ⅒% - Other (not specified) _____ XEC is a child of FLiRT cluster KS.1.1 and FLuQE cluster KP.3.3. XEK is a child of FLiRT31 cluster KP.2.3 and recombinant XEC. XEQ is a child of FLiRT cluster KS.1.1.2 and FLuQE cluster KP.3. XFC is a child of FLiRT31 cluster LP.8.1.1 and FLiRT cluster LF.7. XFG is a child of FLiRT31 cluster LP.8.1.2 and FLiRT cluster LF.7. [Add'l footnotes omitted.]
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sport of sacred spherical cows

Updated #CDC estimates show we'd pretty much been in a JN.1.11 soup since Dec, until late March, when LP.8.1 took majority.

Data collection continues to be a low priority nationally, as exactly zero regions have enough data for CDC to plot.

Two children of LF.7.7, dot1 and dot2, broken out by CDC, together with PA.1, a grandchild of MC.10.

Raj's dashboard was last updated a week ago today.

❖ #ThisIsOurPolio #Covid #Covid19 #SARS2 #variants #CovidIsNotOver #CovidIsAirborne #dataviz #datavis

Chart: Estimated U.S. Variant Proportions by Common Name Sources: Centers for Disease Control, CoV-Lineages, NYITCOM Research, Daniele Focosi, World Health Network, others [ beadsland on Ko-fi ] Reskin of CDC's Variants Nowcast, and any significant variants in GISAID not broken out by CDC. Five bar-style tree-charts, for fortnights through April 13–26. Legend of last fortnight, organized by subheadings of color-grouped families and convergent clusters. Percentages overlay each color key, reflecting share as of most recent tree-chart. Essentially all WHO-Vaccine-Target JN.1. LP.8.1 accounts for over two thirds; JN.1 + FLiRT for near a quarter. For fortnight of 3/30–4/12, packed bubble charts fill single-variant tiles, indicating diversification of those variants (per GISAID) that wouldn't otherwise be apparent from CDC's Nowcast. Legend: LP.8.1 [purple]: 69% - LP.8.1.1 / NY† & other LP.8.1 JN.1 + FLiRT-KS [browns]: 1% - XEC.4 ¾% - XEQ 10% - other XEC JN.1 + FLiRT [reds]: 6% - LF.7.7.2 4% - LF.7.7.1, LF.7 & LF.7.2.1 / PC 2% - LB.1.3.1 / NL JN.1.11 [greens]: 3% - MC.10.1, MC.28.1 & MC.19 2% - PA.1 ½% - KP.3 2% - MC.1 & other KP.3.1.1 / MC XEK [blue]: ⅜% - XEK Other [greys]: ⅙% - JN.1.16 ⅒% - NB.1† & other WHO-Vaccine-Target JN.1 ¼% - Other (not specified) † Dagger variants are not broken out by CDC, yet represent a significant share of recent GISAID sequences.
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Marian Dörk

2-year professorship in »Information Visualization & Management« (Oct 2025–Sep 2027, W2) at #FHPotsdam with focus on data visualization, urban complexity & interdisciplinary research.

This is my parental leave replacement - feel free to reach out to me or @boris if you have any questions.

Applications already due on 9 May!

Job ad: jobs.b-ite.com/jobposting/a595
(this is in German, but teaching can be in English!)

jobs.b-ite.comVertretungsprofessur (W2) »Information Visualization & Management«
#AcademicJobs#DataVis#DataViz
Continued thread
Public
sport of sacred spherical cows

Updated #CDC estimates show we've pretty much been in a JN.1.11 soup since Dec, until late March, when LP.8.1 took majority.

Data collection continues to be a low priority nationally, as exactly zero regions have enough data for CDC to plot.

No new variants broken out, yet CDC seems to have resources to tailor their color key: hcommons.social/@beadsland/114

Raj's dashboard was updated on today.

❖ #ThisIsOurPolio #Covid #Covid19 #SARS2 #variants #CovidIsNotOver #CovidIsAirborne #dataviz #datavis

Chart: Estimated U.S. Variant Proportions by Common Name Sources: Centers for Disease Control, CoV-Lineages, NYITCOM Research, Daniele Focosi, World Health Network, others [ beadsland on Ko-fi ] Reskin of CDC's Variants Nowcast, and any significant variants in GISAID not broken out by CDC. Five bar-style tree-charts, for fortnights through Mar 30–Apr 12. Legend of last fortnight, organized by subheadings of color-grouped families and convergent clusters. Percentages overlay each color key, reflecting share as of most recent tree-chart. Essentially all WHO-Vaccine-Target JN.1. LP.8.1 accounts for over three fifths; JN.1 + FLiRT for near a quarter. For fortnight of 3/16–3/29, packed bubble charts fill single-variant tiles, indicating diversification of those variants (per GISAID) that wouldn't otherwise be apparent from CDC's Nowcast. Legend: LP.8.1 [purple]: 64% - LP.8.1.1 / NY† & other LP.8.1 XEC [browns]: 2% - XEC.4 15% - other XEC JN.1.11 + FLuQE [greens]: 5% - MC.10.1 & MC.19 1% - MC.28.1 2% - XEQ & other KP.3 3% - MC.1 & other KP.3.1.1 / MC JN.1 + FLiRT [reds]: 4% - LF.7 2% - LB.1.3.1 / NL ¾% - LF.7.2.1 / PC JN.1.11 + FLiRT [blues]: ½% - XEK 0% - KP.2.3 Other [greys]: ⅓% - JN.1.16 ⅒% - other WHO-Vaccine-Target JN.1 0% - Other (not specified) † Dagger variant is not broken out by CDC, yet represent a significant share of recent GISAID sequences.
Continued thread
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sport of sacred spherical cows

Updated #CDC estimates show we've pretty much been in a JN.1.11 soup since Dec, until late March, when LP.8.1 took majority.

Data collection continues to be a low priority nationally, as only one region (NY/NJ) has enough data for CDC to plot.

No new variants broken out, yet CDC seems to have resources to tailor their color key: hcommons.social/@beadsland/114

Raj's dashboard was updated on Sunday.

❖ #ThisIsOurPolio #Covid #Covid19 #SARS2 #variants #CovidIsNotOver #CovidIsAirborne #dataviz #datavis

Chart: Estimated U.S. Variant Proportions by Common Name Sources: Centers for Disease Control, CoV-Lineages, NYITCOM Research, Daniele Focosi, World Health Network, others [ beadsland on Ko-fi ] Reskin of CDC's Variants Nowcast, and any significant variants in GISAID not broken out by CDC. Five bar-style tree-charts, for fortnights through March 16–29. Legend of last fortnight, organized by subheadings of color-grouped families and convergent clusters. Percentages overlay each color key, reflecting share as of most recent tree-chart. Essentially all WHO-Vaccine-Target JN.1. LP.8.1 accounts for well over half; JN.1 + FLiRT for over a quarter. For fortnight of 3/2–3/15, packed bubble charts fill single-variant tiles, indicating diversification of those variants (per GISAID) that wouldn't otherwise be apparent from CDC's Nowcast. Legend: LP.8.1 [purple]: 55% - LP.8.1.1 / NY† & other LP.8.1 XEC [browns]: 21% - XEC.2† & other XEC 2% - XEC.4 JN.1.11 + FLuQE [greens]: 6% - MC.10.1 & MC.19 3% - MC.28.1 2% - XEQ 4% - MC.1 & other KP.3.1.1 / MC ⅘% - other KP.3 JN.1 + FLiRT [reds]: 4% - LF.7 2% - LB.1.3.1 / NL JN.1.11 + FLiRT [blues]: ½% - XEK 0% - KP.2.3 & KP.1.1.3 / LP Other [greys]: ⅖% - JN.1.16 ⅙% - other WHO-Vaccine-Target JN.1 0% - Other (not specified) † Dagger variants are not broken out by CDC, yet represent a significant share of recent GISAID sequences.
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sport of sacred spherical cows

A FLuQE wavelet opened September, cresting as KP.3.1.1 / MC wave into November. FDA's second-guess vaccine target, KP.2, dropped out in December. Updated #CDC estimates indicate we've been in a JN.1.11 soup pretty much since then.

No new variants broken out by CDC, as KP.1.1.3 / LP descendant LP.8.1 approaches majority.

No recent GISAID data—as Raj's dashboard hasn't updated in near a month.

❖ #ThisIsOurPolio #Covid #Covid19 #SARS2 #variants #CovidIsNotOver #CovidIsAirborne #dataviz #datavis

Chart: Estimated U.S. Variant Proportions by Common Name Sources: Centers for Disease Control, CoV-Lineages, NYITCOM Research, Daniele Focosi, World Health Network, others [ beadsland on Ko-fi ] Reskin of CDC's Variants Nowcast, and any significant variants in GISAID not broken out by CDC. Five bar-style tree-charts, for fortnights through March 2–15. Legend of last fortnight, organized by subheadings of color-grouped families and convergent clusters. Percentages overlay each color key, reflecting share as of most recent tree-chart. Essentially all WHO-Vaccine-Target JN.1. JN.1.11 accounts for over three fifths; JN.1.11 + FLiRT for near half. For fortnight of 1/19–2/1, packed bubble charts fill single-variant tiles, indicating diversification of those variants (per GISAID) that wouldn't otherwise be apparent from CDC's Nowcast. Legend: LP.8.1 [purple]: 47% - LP.8.1.1 / NY† & other LP.8.1 JN.1 + FLiRT-KS [browns]: 26% - XEC.2†, XEC.8† & other XEC 2% - XEC.4 2% - XEQ ⅒% - other KS.1 JN.1.11 [greens]: ¾% - KP.3 15% - MC.10.1, MC.28.1, MC.19, MC.1 & other KP.3.1.1 / MC JN.1 + FLiRT [reds]: 4% - LF.7 3% - LB.1.3.1 / NL 0% - LB.1 JN.1.11 + FLiRT [blues]: ½% - XEK 0% - KP.2.3 & KP.1.1.3 / LP Other [greys]: ½% - JN.1.16 ⅐% - other WHO-Vaccine-Target JN.1 ⅒% - Other (not specified) † Dagger variants are not broken out by CDC, yet represent a significant share of recent GISAID sequences.
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