Alexander Lex<p>Can you run a think-aloud study via crowdsourcing? Yes you can! We used reVISit for running and analyzing online TA studies. And yes, online participants do actually speak, though they’re more critical than lab participants. Check out the CHI paper: <a href="https://vdl.sci.utah.edu/publications/2025_chi_crowdaloud/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">vdl.sci.utah.edu/publications/</span><span class="invisible">2025_chi_crowdaloud/</span></a> <a href="https://vis.social/tags/datavis" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>datavis</span></a> <a href="https://vis.social/tags/chi2025" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>chi2025</span></a></p>
Recent searches
Search options
#datavis
0 posts0 participants0 posts today
"Fun" fact I came across when reading about violence against women from Indigenous communities in North America - the US is one of only a few countries worldwide that has not managed to agree on adopting the UN bill for women's rights, despite multiple attempts in the past 45 years.
Um...why is the Outlier conference taking place in Miami again this year?
Wouldn't it be safer to hold it in a place that will be less likely to be hit by a series of storms? Yeah, I know there aren't any perfect alternatives. But aren't there better options?
We’ve released reVISit 2.0 (http://revisit.dev), the latest version of our open user study platform! There are a LOT of awesome new things in this release that will not only make it easier to run your user study for #ieeevis, but give you new analysis capabilities. #datavis
https://www.youtube.com/watch?v=wjP35gra9J4
revisit.devHome | ReVISitreVISit: Reproducible and Powerful Visualization User Studies
A FLuQE wavelet opened September, becoming MC wave into November. December saw both FLiRT clans and JN.1.11 vie for dominance, only for JN.1 FLiRT to win out.
After skipping update two weeks prior, #CDC broke out XEC.4, as FLiRT KS.1.1 / FLuQE KP.3.3 hybrid XEC family—never having reached majority—being pressed by FLiRT LP.8.1.
New dashboard from Raj givs us more recent GISAID data.
❖ #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 January 5–18. 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 + FLiRT accounts for well over half; XEC for near half.
For fortnight of 12/22–1/4, 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:
XEC [blues]:
47% - XEC.2† & other XEC
3% - XEC.4
JN.1.11 [purples]:
1% - KP.3
23% - MC.10.1, MC.1, MC.19 & other KP.3.1.1 / MC
JN.1.11 + FLiRT-LP [browns]:
15% - LP.8.1
⅛% - LP.1 & other KP.1.1.3 / LP
JN.1 + FLiRT [greens]:
4% - LF.7
2% - LB.1.3.1 / NL
1% - JN.1.18.6 / LY
⅒% - LB.1
JN.1.11 + FLiRT [reds]:
4% - XEK
⅒% - FDA-Vaccine-Target KP.2
⅑% - other KP.2.3
Other [greys]:
⅒% - other WHO-Vaccine-Target JN.1
⅒% - Other (not specified)
† Dagger variant is not broken out by CDC, yet represent a significant share of recent GISAID sequences.](https://spaces.hcommons.social/media_attachments/files/113/871/149/086/456/148/original/ab960ae7a01a0789.jpg "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 January 5–18. 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 + FLiRT accounts for well over half; XEC for near half.
For fortnight of 12/22–1/4, 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:
XEC [blues]:
47% - XEC.2† & other XEC
3% - XEC.4
JN.1.11 [purples]:
1% - KP.3
23% - MC.10.1, MC.1, MC.19 & other KP.3.1.1 / MC
JN.1.11 + FLiRT-LP [browns]:
15% - LP.8.1
⅛% - LP.1 & other KP.1.1.3 / LP
JN.1 + FLiRT [greens]:
4% - LF.7
2% - LB.1.3.1 / NL
1% - JN.1.18.6 / LY
⅒% - LB.1
JN.1.11 + FLiRT [reds]:
4% - XEK
⅒% - FDA-Vaccine-Target KP.2
⅑% - other KP.2.3
Other [greys]:
⅒% - other WHO-Vaccine-Target JN.1
⅒% - Other (not specified)
† Dagger variant is not broken out by CDC, yet represent a significant share of recent GISAID sequences.")
The fires in LA now cover an area larger than 40,000 acres, a huge swath of land roughly the size of Washington, DC.
Still having a hard time visualizing the size? Use my latest interactive map for CalMatters to compare it to a place you know much better: where you live.
https://calmatters.org/environment/wildfires/2025/01/la-fires-size-mapped/
CalMatters · Map: How big are the LA fires? Use this tool to overlay them atop where you liveTo better understand the size of the LA fires, our tool lets you overlay the fire perimeters on any location in California.
it's the end of the work week
a good time to follow a few folks for visualization inspiration – in case you do not know them yet:
#30DayMapChallenge Day 21 - Conflict 
In case anyone needed a reminder: there is no neutral map! (I did - I have uncritically resorted to the Natural Earth map way too often just because it's so easy to load it in R).
#30DayMapChallenge Day 1 (yes, i'm very behind) - Points 
Almost half of this planet's population still lives in poverty. I need to be reminded of this basic fact even while the choropleth maps about poverty rates are very familiar to me. I'm not sure if turning people into points makes it any better, but at least the process of doing so made me think a bit more about the numbers and lives behind the data.
#30DayMapChallenge Day 11 - Arctic 
In which country do most people live in the Arctic?
Once again, have only had opportunity to add hundred or so lines to #AnnoPlot project since the last update:
https://hcommons.social/@beadsland/113218241027273518
In our post-data era, only variants #dataviz is still actively being updated.
Maintenance includes: cosmetic tweaks to bubbles and embossing; tweaks to label order, bundle logic, and legend families; debugging cluster and recombinants parent tracing; & general refactoring.
Unfortunately, ongoing fires in personal life means little time for #datavis programming.
![Chart: Annoplot Dataviz Library*: Project Profile
Subtitle: 10.3K 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 wedges associated with variants chart, esp. variants/tree, are variously exploded out.
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 2024-11-09.
† Python, Markdown, C, and Elixir source files. Blank lines omitted form tallies.
Exploded wedges reflect proportions of lines changed in last 30 days. Dotted areas represent non-blank comment lines and Markdown.
Wedges:
🔴 levels
🧀 [blank wedge] - 460, 🧀 hospitals - 282
🟣 chirp
🧀 [blank] - 290, 🧀 audio - 241
🔵 annoplot
🧀 [blank] - 540, 🧀 artists - 351, 🧀 artists/deco - 503, 🧀 artists/legend - 303, 🧀 artists/pie - 287, 🧀 artists/text - 316, 🧀 coord - 592, 🧀 coord/base - 259, 🧀 margin - 255, 🧀 util - 475
🟢 tiop
🧀 [blank] - 244, 🧀 bullseye - 321, 🧀 capacity - 455, 🧀 devpie - 426, 🧀 devpie/slice - 230, 🧀 variants - 438, 🧀 variants/orchard - 412, 🧀 variants/rajdash - 326, 🧀 variants/tree - 573
🟤 bots
🧀 [blank] - 146, 🧀 talky - 75, 🧀 talky/talky - 746
⚫ . [period by itself]
🧀 [blank] - 406, 🧀 TODO.md - 348](https://spaces.hcommons.social/media_attachments/files/113/456/606/371/101/669/original/2066504fb39c8743.jpg "Chart: Annoplot Dataviz Library*: Project Profile
Subtitle: 10.3K 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 wedges associated with variants chart, esp. variants/tree, are variously exploded out.
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 2024-11-09.
† Python, Markdown, C, and Elixir source files. Blank lines omitted form tallies.
Exploded wedges reflect proportions of lines changed in last 30 days. Dotted areas represent non-blank comment lines and Markdown.
Wedges:
🔴 levels
🧀 [blank wedge] - 460, 🧀 hospitals - 282
🟣 chirp
🧀 [blank] - 290, 🧀 audio - 241
🔵 annoplot
🧀 [blank] - 540, 🧀 artists - 351, 🧀 artists/deco - 503, 🧀 artists/legend - 303, 🧀 artists/pie - 287, 🧀 artists/text - 316, 🧀 coord - 592, 🧀 coord/base - 259, 🧀 margin - 255, 🧀 util - 475
🟢 tiop
🧀 [blank] - 244, 🧀 bullseye - 321, 🧀 capacity - 455, 🧀 devpie - 426, 🧀 devpie/slice - 230, 🧀 variants - 438, 🧀 variants/orchard - 412, 🧀 variants/rajdash - 326, 🧀 variants/tree - 573
🟤 bots
🧀 [blank] - 146, 🧀 talky - 75, 🧀 talky/talky - 746
⚫ . [period by itself]
🧀 [blank] - 406, 🧀 TODO.md - 348")
In Aug, summer FLiRT wave receded into S:F546L soup. Sept FLuQE wavelet matured into Oct MC wave. Now that #CDC has corrected Friday's public data, we see XEC—spawn of FLiRT KS.1.1 & FLuQE KP.3.3—poised to displace MC in November.
Meanwhile, FLiRT LB.1.3.1 has a new alias. We're in the second half of the alphabet.
Latest GISAID is sparse, so significance of MC.10 and LF.1.7 likely anomalous.
❖ #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, D. Focosi, WHN, others
[ beadsland on Ko-fi ]
A reskin of CDC's Variants Nowcast, emphasizing significant variants, incl. those in GISAID yet not broken out by CDC.
Five rectangular tree-charts, side by side, for fortnights through October 27–November 9. Legend 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 JN.1. KP.3 fam accounts for near two thirds of total, KP.3.1.1 alone over half.
For week of 10/13–11/9, packed bubble charts fills larger single-variant tiles, indicating diversification of those variants—per GISAID—that wouldn't otherwise be apparent given CDC's choices of what to break out or not.
Legend:
JN.1.11 + FLuQE31-MC [blue]:
52% - MC.10† & other KP.3.1.1 / MC
6% - MC.1
JN.1.11 + FLiRT-KS [purples]:
26% - XEC
⅒% - KS.1
JN.1 + FLiRT [reds]:
3% - LB.1.7†, LF.3.1 & other JN.1.16.1 / LF
2% - LB.1
2% - LB.1.3.1 / NL
JN.1.11 + FLiRT [browns]:
3% - KP.2.3 & KP.2.15
1% - FDA-Vaccine-Target KP.2, KP.1.1 & KP.4.1
⅖% - LP.1
⅝% - other KP.1.1.3 / LP
JN.1.11 + FLuQE [green]:
3% - KP.3
Other [greys]:
½% - JN.1.18, JN.1.11.1 / KP & four tracked variants at <⅒%
0% - Pirola + FViRT
0% - Hippogryph XBB
1% - other WHO-Vaccine-Target JN.1
½% - Other (not specified)](https://spaces.hcommons.social/media_attachments/files/113/450/818/397/283/795/original/b899ac6ba4fac594.jpg "Chart: Estimated U.S. Variant Proportions by Common Name
Sources: Centers for Disease Control, CoV-Lineages, NYITCOM, D. Focosi, WHN, others
[ beadsland on Ko-fi ]
A reskin of CDC's Variants Nowcast, emphasizing significant variants, incl. those in GISAID yet not broken out by CDC.
Five rectangular tree-charts, side by side, for fortnights through October 27–November 9. Legend 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 JN.1. KP.3 fam accounts for near two thirds of total, KP.3.1.1 alone over half.
For week of 10/13–11/9, packed bubble charts fills larger single-variant tiles, indicating diversification of those variants—per GISAID—that wouldn't otherwise be apparent given CDC's choices of what to break out or not.
Legend:
JN.1.11 + FLuQE31-MC [blue]:
52% - MC.10† & other KP.3.1.1 / MC
6% - MC.1
JN.1.11 + FLiRT-KS [purples]:
26% - XEC
⅒% - KS.1
JN.1 + FLiRT [reds]:
3% - LB.1.7†, LF.3.1 & other JN.1.16.1 / LF
2% - LB.1
2% - LB.1.3.1 / NL
JN.1.11 + FLiRT [browns]:
3% - KP.2.3 & KP.2.15
1% - FDA-Vaccine-Target KP.2, KP.1.1 & KP.4.1
⅖% - LP.1
⅝% - other KP.1.1.3 / LP
JN.1.11 + FLuQE [green]:
3% - KP.3
Other [greys]:
½% - JN.1.18, JN.1.11.1 / KP & four tracked variants at <⅒%
0% - Pirola + FViRT
0% - Hippogryph XBB
1% - other WHO-Vaccine-Target JN.1
½% - Other (not specified)")
In Aug, summer FLiRT wave receded into S:F546L soup. Sept FLuQE wavelet matured into Oct MC wave. Now that #CDC has corrected Friday's public data, we see XEC—spawn of FLiRT KS.1.1 & FLuQE KP.3.3—poised to displace MC in November.
Meanwhile, FLiRT LB.1.3.1 has a new alias. We're in the second half of the alphabet.
Latest GISAID data shows no significant variants not already broken out by CDC.
❖ #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, D. Focosi, WHN, others
[ beadsland on Ko-fi ]
A reskin of CDC's Variants Nowcast, emphasizing significant variants, incl. those in GISAID yet not broken out by CDC.
Five rectangular tree-charts, side by side, for fortnights through Oct 13–Oct 26. Legend 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 JN.1. KP.3 fam accounts for near two thirds of total, KP.3.1.1 alone over half.
For week of 9/29–10/12, packed bubble charts fills larger single-variant tiles, indicating diversification of those variants—per GISAID—that wouldn't otherwise be apparent given CDC's choices of what to break out or not.
Legend:
JN.1.11 + FLuQE31-MC [blues]:
5% - MC.1
57% - other KP.3.1.1 / MC
JN.1 + FLiRT-KS [reds]:
17% - XEC
⅕% - other KS.1
JN.1.11 + FLiRT [browns]:
5% - KP.2.3 & KP.2.15
2% - FDA-Vaccine-Target KP.2, KP.1.1 & KP.4.1
2% - LP.1 & other KP.1.1.3 / LP
JN.1 + FLiRT [purples]:
5% - LB.1, JN.1.16.1 / LF & LF.3.1
2% - LB.1.3.1 / NL
JN.1.11 + FLuQE [green]:
3% - KP.3
Other [greys]:
¾% - JN.1.18
0% - Hyperion XBB.1.9.1 / FL & Kraken XBB.1.5
0% - Pirola + FViRT31
⅖% - JN.1.11.1 / KP, four tracked variants at <⅒% & other WHO-Vaccine-Target JN.1
0% - other Omicron-2 BA.2
½% - Other (not specified)](https://spaces.hcommons.social/media_attachments/files/113/388/316/400/849/171/original/9c267a7f5b4ddde9.jpg "Chart: Estimated U.S. Variant Proportions by Common Name
Sources: Centers for Disease Control, CoV-Lineages, NYITCOM, D. Focosi, WHN, others
[ beadsland on Ko-fi ]
A reskin of CDC's Variants Nowcast, emphasizing significant variants, incl. those in GISAID yet not broken out by CDC.
Five rectangular tree-charts, side by side, for fortnights through Oct 13–Oct 26. Legend 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 JN.1. KP.3 fam accounts for near two thirds of total, KP.3.1.1 alone over half.
For week of 9/29–10/12, packed bubble charts fills larger single-variant tiles, indicating diversification of those variants—per GISAID—that wouldn't otherwise be apparent given CDC's choices of what to break out or not.
Legend:
JN.1.11 + FLuQE31-MC [blues]:
5% - MC.1
57% - other KP.3.1.1 / MC
JN.1 + FLiRT-KS [reds]:
17% - XEC
⅕% - other KS.1
JN.1.11 + FLiRT [browns]:
5% - KP.2.3 & KP.2.15
2% - FDA-Vaccine-Target KP.2, KP.1.1 & KP.4.1
2% - LP.1 & other KP.1.1.3 / LP
JN.1 + FLiRT [purples]:
5% - LB.1, JN.1.16.1 / LF & LF.3.1
2% - LB.1.3.1 / NL
JN.1.11 + FLuQE [green]:
3% - KP.3
Other [greys]:
¾% - JN.1.18
0% - Hyperion XBB.1.9.1 / FL & Kraken XBB.1.5
0% - Pirola + FViRT31
⅖% - JN.1.11.1 / KP, four tracked variants at <⅒% & other WHO-Vaccine-Target JN.1
0% - other Omicron-2 BA.2
½% - Other (not specified)")