Venkatesh Potluri, Sudheesh Singanamalla, Nussara Tieanklin, Jennifer Mankoff: Notably Inaccessible – Data Driven Understanding of Data Science Notebook (In)Accessibility. ASSETS 2023: 13:1-13:19

Computational notebooks are tools that help people explore, analyze data, and create stories about that data. They are the most popular choice for data scientists. People use software like Jupyter, Datalore, and Google Colab to work with these notebooks in universities and companies.

There is a lot of research on how data scientists use these notebooks and how to help them work together better. But there is not much information about the problems faced by blind and visually impaired (BVI) users. BVI users have difficulty using these notebooks because:

• The interfaces are not accessible.
• The way data is shown is not user-friendly for them.
• Popular libraries do not provide outputs they can use.

We analyzed 100,000 Jupyter notebooks to find accessibility problems. We looked for issues that affect how these notebooks are created and read. From our study, we give advice on how to make notebooks more accessible. We suggest ways for people to write better notebooks and changes to make the notebook software work better for everyone.