maidr

Overview

maidr (Multimodal Access and Interactive Data Representation) makes data visualizations accessible to users with visual impairments. It converts ggplot2 and Base R plots into interactive, accessible HTML/SVG formats with keyboard navigation, screen reader support, and sonification. maidr for R is the R binding of MAIDR, the JavaScript core developed by the (x)Ability Design Lab at the University of Illinois Urbana-Champaign; the same accessibility layer is available for Python as py-maidr.

The package provides two main functions:

• show() displays an interactive accessible plot in RStudio Viewer or browser
• save_html() writes a plot to an HTML file, with the MAIDR.js library in a lib/ folder beside it

Installation

maidr requires R 4.0.0 or later. Install the stable release from CRAN:

install.packages("maidr")

Or install the development version from GitHub:

# Using pak (recommended)
pak::pak("xability/r-maidr")

# Alternative: using pacman (auto-installs if missing)
pacman::p_load_gh("xability/r-maidr")

Usage

ggplot2

library(maidr)
library(ggplot2)

p <- ggplot(mpg, aes(x = class)) +
  geom_bar(fill = "steelblue") +
  labs(title = "Vehicle Classes", x = "Class", y = "Count")

# Display interactive accessible plot
show(p)

# Or save to file
save_html(p, "vehicle_classes.html")

Base R

library(maidr)

# Create plot first
barplot(
  table(mtcars$cyl),
  main = "Cars by Cylinder Count",
  xlab = "Cylinders",
  ylab = "Count"
)

# Then call show() without arguments
show()

plotly, highcharter and echarts4r widgets

maidr_htmlwidget() makes an interactive chart from plotly (plot_ly(), ggplotly()), highcharter or echarts4r accessible. The chart is read in the browser by the MAIDR adapter for the library that draws it, so it works wherever the widget does: the viewer, htmlwidgets::saveWidget(), R Markdown, Quarto and Shiny.

library(maidr)
library(plotly)

plot_ly(mtcars, x = ~wt, y = ~mpg, type = "scatter", mode = "markers") |>
  maidr_htmlwidget()

# ggplotly() keeps your ggplot2 code
ggplotly(ggplot(mtcars, aes(wt, mpg)) + geom_point()) |>
  maidr_htmlwidget()

An echarts4r chart is switched to ECharts’ SVG renderer, which MAIDR needs to highlight the mark being read. While an echarts4r chart shows its legend, the visual highlight is off; audio, text and braille are not affected.

How maidr hooks into your session

• Console. library(maidr) is all it takes. Printing a ggplot2 object, by typing p or print(p), opens it in the maidr viewer; show(p) is the explicit form. Base R plotting calls are recorded, and show() with no argument opens the recorded chart. save_html() writes either kind to a file.
• R Markdown and Quarto. Call maidr_on() once in a setup chunk. It installs the knitr hooks that turn every plot the document draws into an accessible chart; library(maidr) alone does not install them.
• Shiny. Put maidr_output() in the UI and render_maidr() in the server; see vignette("shiny-integration", package = "maidr").
• Turning it off. maidr_off() stops interception for the session and maidr_on() starts it again. options(maidr.ggplot2 = FALSE) leaves ggplot2 printing alone, options(maidr.base_r = FALSE) stops recording Base R calls, and options(maidr.auto_show = FALSE), in .Rprofile to make it permanent, turns everything off. See ?"maidr-options".
• What gets masked. Attaching maidr puts its own copies of the Base R plotting functions, and of methods::show(), ahead of the originals; R lists them at library(maidr). Each records the call and passes through to the original, and show() hands anything that is not a plot back to methods::show(). In a script or a package call maidr::show() by name, and attach vioplot, wordcloud or quantmod before maidr, or their own functions mask the wrappers and their charts go unrecorded. See ?"base-r-wrappers".

Supported plot types

maidr supports a wide range of visualization types in both ggplot2 and Base R:

Basic Plot Types

Note: Volume bars and moving-average overlays for candlestick charts are supported only on the ggplot2 + {tidyquant} + {patchwork} path. On the Base R path, quantmod::chartSeries() TA overlays (addVo(), addSMA(), addEMA()) — and the default TA whenever the input xts carries a Volume column — fall back to native (non-accessible) graphics with a one-time advisory.

Advanced Plot Types

Experimental Plot Types

[!WARNING] These are prototypes. Treat them as prototypes. They are under active development, they are unstable, and none of them has been through a user study. Field names, announcement wording and navigation may change without a deprecation period, including in a patch release. If you are building something that has to keep working, build it on the plot types above.

Everything in the two tables above predates the plot coverage roadmap (#137) and has been exercised by real readers over real charts. Everything below was added by that roadmap and the base R sweeps that followed it (#251, #262), most inside a few weeks.

Each was measured against the chart it reads — that is what the issues and the tests record. But measuring that a reading is faithful to the drawing is a different claim from establishing that it is useful to a reader. Nobody has asked a blind or low-vision reader whether hearing stars() as a radar, or navigating a termplot() panel by panel, is the right way to read one. Until that happens these are proposals about how a chart could be read, not answers.

Feedback is exactly what would move one of these into the tables above.

Elsewhere in these docs — the example articles, the getting-started vignette and the package help — an experimental type is marked [experimental] after its name; a type with no mark is stable. Wherever they list plot types, the stable ones come first and the experimental ones follow in a section of their own, as they do here.

ggplot2

Base R

The split is the diff of each factory’s get_supported_types() against 8de0e98, the last commit on main before #137 was filed. tests/testthat/test-plot-type-stability.R fails if a supported type appears in neither the stable tables nor the experimental ones, so a new layer type has to be placed deliberately rather than inherit either promise by being forgotten.

The JavaScript core and the Python binding make the same distinction over their own type lists, with the same boundary and for the same reason, and mark their docs the same way: see the JavaScript core’s trace type stability and the Python binding’s stability page.

See the examples gallery for a worked example of each plot type.

Accessibility features

• Keyboard navigation - explore data points using arrow keys
• Screen reader support - full ARIA labels and live announcements
• Sonification - hear data patterns through sound
• Text descriptions - automatic statistical summaries

The keys a reader needs first, the same on every page of this documentation:

Every other shortcut, including autoplay, jumping to the ends, the command palette, settings and the AI chat, is on the MAIDR controls reference.

Offline support

By default, show() and save_html() use the bundled maidr.js library, so the result works offline. save_html() writes the library to a lib/ folder beside the file, and the two have to be shared together: zip the folder that holds both, or copy both. An .html sent on its own loads no maidr.js and shows a plain, inaccessible chart. Widgets, knitr documents and Shiny apps auto-detect internet availability and use the CDN when online. A knitted R Markdown or Quarto document rendered online, and any page holding a widget, also carries its own copy of maidr.js, which its charts fall back on when the CDN cannot be reached, so a self_contained / embed-resources document works offline too. Use the use_cdn parameter for explicit control:

# Force CDN: one self-contained file, needs internet whenever it is viewed
show(p, use_cdn = TRUE)
save_html(p, "plot.html", use_cdn = TRUE)

# Force bundled files: works offline, lib/ folder beside the saved file
show(p, use_cdn = FALSE)
save_html(p, "plot.html", use_cdn = FALSE)

The CDN paths load the latest published maidr.js, not the copy bundled with this package, as the Python binding does. The first CDN document in an R session asks jsDelivr (then the npm registry) which version that is, within 3 seconds, and every document in the session names that version. If the lookup cannot be made it costs no error: the document names the bundled version instead, the copy use_cdn = FALSE would serve. Pin a version when a document has to load the same maidr.js whenever it is opened:

options(maidr.cdn_version = "bundled")  # the bundled version, no lookup
options(maidr.cdn_version = "4.9.0")    # a particular release

or set MAIDR_CDN_VERSION in the environment. use_cdn = FALSE never makes that lookup. See ?"maidr-options".

Two things still reach the network from an offline document, and only when a reader uses them. One is a language other than English. maidr.js reads charts in English on its own and fetches Korean, Japanese, Chinese, Spanish, German, French, Italian or Hindi as a small pack from beside itself. This package does not bundle the packs, which would add 0.8 MB against CRAN’s size limit, so a use_cdn = FALSE document points maidr.js at the packs of the bundled version on jsDelivr: a reader whose language is not English hears it when online, and English when not. Serve the packs yourself, or turn this off:

options(maidr.locale_base_url = "https://example.org/maidr/")  # your own copy
options(maidr.locale_base_url = FALSE)  # never fetch a pack: English only

The other is connecting a DotPad tactile display. maidr.js does not bundle the DotPad SDK, whose braille engine is a 14 MB liblouis build, and imports the vendor’s copy from jsDelivr the first time a DotPad is connected. Rendering, sonification and braille work offline regardless. To keep the DotPad offline too, download the pinned SDK once and every use_cdn = FALSE document carries it in its lib/ folder:

maidr_download_dotpad_sdk()          # ~14 MB, once, into a per-user cache
save_html(p, "plot.html", use_cdn = FALSE)   # lib/dotpad-sdk-<version>/ beside it

A page served from elsewhere, or a knitr document (whose charts live in srcdoc frames with no base URL), names its copy by URL instead, through options or the environment variables of the same names:

options(
  maidr.dotpad_sdk_url = "https://intranet.example/dotpad/DotPadSDK-3.0.3.js",
  maidr.dotpad_asset_base_url = "https://intranet.example/dotpad/lib/"
)
# or: Sys.setenv(MAIDR_DOTPAD_SDK_URL = "...", MAIDR_DOTPAD_ASSET_BASE_URL = "...")

Every document maidr produces then declares window.MAIDR_DOTPAD_SDK_URL and window.MAIDR_DOTPAD_ASSET_BASE_URL ahead of maidr.js. See ?"maidr-options".

Getting help

• Report bugs or request features at GitHub Issues
• Browse the function reference, or run help(package = "maidr") offline

Learning more

• vignette("getting-started", package = "maidr") for an introduction
• The examples gallery for supported visualizations
• vignette("shiny-integration", package = "maidr") for Shiny apps
• The maidr skill for AI coding agents (Claude Code, Codex, Cursor, and others): once installed with npx skills add xability/maidr-skill, an agent that writes ggplot2 or base R plotting code routes the result through this package so the chart comes out accessible

Related projects

maidr for R is one of three MAIDR packages, all developed by the (x)Ability Design Lab at the University of Illinois Urbana-Champaign:

• MAIDR JavaScript core, the TypeScript engine (npm package maidr) that renders every accessible chart, including the ones this package produces.
• py-maidr for Python, the Python binding for matplotlib, seaborn, Plotly and Altair (PyPI package maidr).
• maidr for R, this package, for ggplot2 and Base R graphics (CRAN package maidr; source at xability/r-maidr).

Citation

If you use maidr in research, please cite the MAIDR papers:

• Seo, J., Xia, Y., Lee, B., Mccurry, S., & Yam, Y. J. (2024). MAIDR: Making Statistical Visualizations Accessible with Multimodal Data Representation. In Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI ’24). ACM. https://doi.org/10.1145/3613904.3642730
• Seo, J., O’Modhrain, S., Xia, Y., Kamath, S., Lee, B., & Coughlan, J. M. (2024). Designing Born-Accessible Courses in Data Science and Visualization: Challenges and Opportunities of a Remote Curriculum Taught by Blind Instructors to Blind Students. In EuroVis 2024 - Education Papers. The Eurographics Association. https://doi.org/10.2312/eved.20241053

citation("maidr") prints both, plus an entry for the package itself, in text and BibTeX form.