[NABS-L] Fwd: [NFBCS] Invitation to Alpha Test: maidr - Accessible Multimodal Data Visualization Python Package for Matplotlib, Seaborn, Jupyter, Google Colab, and More

[Gene Kim]

If you regularly use data analytics/visualizations, consider supporting a
fantastic up and coming Python tool. This project is being lead by one of
the most expert blind engineers/scientists I know.

Cheers,
Gene


---------- Forwarded message ---------
From: xability lab via NFBCS <nfbcs at nfbnet.org>
Date: Tue, Dec 10, 2024 at 4:12 PM
Subject: [NFBCS] Invitation to Alpha Test: maidr - Accessible Multimodal
Data Visualization Python Package for Matplotlib, Seaborn, Jupyter, Google
Colab, and More
To: nfbcs at nfbnet.org <nfbcs at nfbnet.org>
Cc: xability lab <xability-lab at illinois.edu>


Hello NFB CS,



Today, we are thrilled to announce that (x)Ability Design Lab at the
University of Illinois Urbana-Champaign is ready to invite you to the alpha
test of our multimodal data representation Python package, called "maidr."



maidr (pronounced as 'mader') stands for multimodal access and interactive
data representation. This is an accessible framework for multimodal data
representation. With maidr, blind and sighted users can easily augment data
visualizations into touchable (Braille), readable (text), audible
(sonification), and conversational (AI) formats that work for both screen
readers and refreshable braille displays.



The following summarizes the key features and design principles of maidr
for Python:



1. Accessibility: maidr is designed to be accessible to both blind and
sighted users from the ground up. Beyond the passive consumption level,
blind users can also independently create, modify, and share data
visualizations with others.



2. Inclusivity: maidr does not pursue a special version for blind users.
Instead, it provides a unified interface that supports both visual and
non-visual data exploration. This way, blind and sighted users can work
together on the same data science projects.



3. Integration: maidr seamlessly integrates with the popular and mainstream
data science environments (e.g., Python, pandas, and NumPy) as well as data
visualization libraries in Python like matplotlib and seaborn.



4. Unintrusiveness: maidr does not require changes to existing core data
visualization code. Without needing to reconstruct an accessible version
separately, you can just import maidr package and use maidr.show() to your
plots. Blind and sighted users can use and share the same visualization
codebase in their shared data science projects.



5. Synchronization: maidr treats visualization as one of the multimodal
data representations and ensures that all representations (e.g., visual,
tactile, textual, audible) cursor and braille routing key positions are
synchronized across different modalities.



6. Reactivity: maidr supports widely adopted reactive and interactive
computing including Jupyter Notebooks, Jupyter Labs, Google Colab,
Streamlit dashboard, and Shiny dashboard. maidr also supports interactive
computing inside code editors, such as Visual Studio Code.



7. Reproducibility: maidr supports the generation of accessible data
visualizations as part of the reproducible data science workflow with
Quarto scientific publishing system. You can easily create accessible data
representations within your reproducible reports, website blogs, slides,
e-books, dashboards, and more.



8. Scalability: maidr supports a wide range of data visualization types,
including bar plots, histograms, line plots, box plots, heatmaps, scatter
plots, and more. maidr is designed to be extensible to support new
visualization types. [Multi-figure and multi-layer visualizations are
underway to support complex data visualizations.]



We believe that by making data visualizations accessible, we can empower
blind and sighted users to work together on data science projects, share
insights, and make data-driven decisions collaboratively.



We are currently looking for alpha testers to provide feedback on maidr for
Python. If you are interested in participating in the alpha test, please
fill out the following Google form:



* Blind and low-vision users:
https://docs.google.com/forms/d/e/1FAIpQLScvOkEkOvOflqJpZ-nEkntt8hcuqZIw0bGzz6a0p1ONkxfJUw/viewform
<https://urldefense.com/v3/__https:/docs.google.com/forms/d/e/1FAIpQLScvOkEkOvOflqJpZ-nEkntt8hcuqZIw0bGzz6a0p1ONkxfJUw/viewform__;!!DZ3fjg!-JmGCbFSiaLdALUNucjLJerGG8sOw_ouj_r6CW7lehb8PqWhwh4Oa3jmrlnN5v9ynpdScTKfq1caTa6Tcwo44KiMp9nyf56pQg$>



* Sighted users:
https://docs.google.com/forms/d/e/1FAIpQLSfKq9pva8LDzrTkh77zfTV1F63aQaN40cCMQTqVZRcKqC58mQ/viewform
<https://urldefense.com/v3/__https:/docs.google.com/forms/d/e/1FAIpQLSfKq9pva8LDzrTkh77zfTV1F63aQaN40cCMQTqVZRcKqC58mQ/viewform__;!!DZ3fjg!-JmGCbFSiaLdALUNucjLJerGG8sOw_ouj_r6CW7lehb8PqWhwh4Oa3jmrlnN5v9ynpdScTKfq1caTa6Tcwo44KiMp9n20JTZjw$>



We will invite selected participants to the alpha test and provide detailed
instructions and resources in a separate groups.io thread.



Please feel free to share this announcement with your colleagues, friends,
and networks who might be interested in accessible data visualization.



All the best,



JooYoung Seo

Assistant Professor

(x)Ability Design Lab

School of Information Sciences

University of Illinois Urbana-Champaign

https://xabilitylab.ischool.illinois.edu/


_______________________________________________
NFBCS mailing list
NFBCS at nfbnet.org
http://nfbnet.org/mailman/listinfo/nfbcs_nfbnet.org
To unsubscribe, change your list options or get your account info for NFBCS:
http://nfbnet.org/mailman/options/nfbcs_nfbnet.org/gene.sh.kim%40gmail.com