All good things must come to an end, and Jupyter accessibility workshops are no exception. While I may be sad that this series is over, there are many, many things to celebrate and more to look forward to! Let’s break it up into what we did, what we’ve learned, and what we’re going to do in the future.

A quick recap: Jupyter accessibility workshops were a series of events where we connected Jovyans, accessibility experts, and the wider open-source ecosystem for learning and practice in improving accessibility across Jupyter projects. For more specifics on the events individually, visit the January and March event announcements.

What we did

We gathered, we learned, we contributed fixes, all with a dose of laughter. Across three events, our attendees were small in number but mighty, greeting our corner of the internet with

• 1 fantastic captioner
• 2 expert accessibility talks from Frank Elavsky and Eric Bailey
• 3 Saturdays
• 4 first-time contributors to Jupyter projects
• 5 Jupyter projects discussed to better understand how we can support the ecosystem’s accessibility needs as a whole
• 6 hours of events
• 25 participants, with several friendly faces appearing for more than one event
• 88 image descriptions written (contributed between Juptyer documentation and Jupyter.org)
• ~1000 smiles

What a busy season!

We kicked off the events with the knowledge of Frank Elavsky. This included an energetic discussion around the ways that data visualization is already an accessibility accommodation, how to prioritize user feedback and needs, and how to repurpose or reconfigure what we already have to something accessible.

For the second event, our community contributed accessibility fixes to Jupyter projects in the form of image descriptions. This event not only introduces these descriptions — usually alt text — but gives participants a chance to try it out for themselves. Practice always leads to more questions and great conversations, like how to handle long documentation diagrams or when the documentation might benefit from removing an image.

We regrouped in March to learn from Eric Bailey’s vast accessibility experience and to better understand the discussion from a wider perspective. He gave us wonderful examples of accessibility efforts from history, as well as inspiration for how to continue our community’s efforts.

You can find all event resources by date at the following links:

What we learned

With such a rich mix of people and the spotlight on some wonderful speakers, these workshops were privy to discussions at the intersection of digital accessibility and open source. Here are the biggest themes that emerged across all the events.

• Guidelines are the floor. not the ceiling. Creating a pleasant accessible experience will require more than sticking to guidelines.
• Do it, don’t just read about it. Once we started trying to describe Jupyter images, the best questions and discussions appeared.
• It’s all about context. What an image is communicates is determined by what is around it; use this to write good descriptions.
• Don’t be afraid mistakes. Because accessibility still isn’t the norm in many open source spaces, expect to be trying, failing, and iterating.
• Listen to community members first! If they say communicate accessibility failures that are blocking them, prioritize those efforts when you can.

What’s next

Accessibility in Jupyter spaces is far from over, and we’d love to have you find your new favorite place on the internet here. Just as Jupyter is not a single project, accessibility goes beyond what we covered in the workshops.

We started somewhere designed to be approachable for people of all experience levels, but the next major steps include prioritizing the feedback of disabled people in Jupyter, solving existing issues across projects, and creating methods for sustainable accessibility within our community. These problems won’t be solved with Jupyter knowledge alone, accessibility experience alone, code sorcery alone, documentation brilliance alone, or any other single skill set alone. But they can be solved together. Bring your skills with you, and we can find a place for you here!

If you’d like to get more involved with accessibility efforts, feel free to join our community via

• The jupyter/accessibility GitHub repository, a place for gathering cross-project on GitHub.

• Jupyter’s Discourse section for accessibility, a place for gathering cross-project separate from Jupyter codebases.

• Fortnightly JupyterLab accessibility meetings (found on the community calendar).

• For JupyterLab efforts, visit the JupyterLab accessibility GitHub project, where issues and pull requests for are listed.

• Open a GitHub issue to propose an accessibility change (please check if a similar issue already exists and add a comment to that one if possible).