Improving accessibility for data science with graph sonification library


Prior knowledge:
No previous knowledge expected


This talk will introduce the graph sonification library, developed for people who are trying to learn data science by relying only on audio. It will then provide an opportunity to think about the accessibility of data science.


Using graphs to efficiently analyze huge amounts of data is an essential part of learning data science. However, for developers who are blind or have difficulty seeing, these visually dependent methods are a major barrier to learning data science. Therefore, in order to support a non-visually dependent learning environment, I have released a library that outputs data as a sonified graph with a simple interface, similar to popular graph libraries such as matplotlib. In this presentation, I will introduce the features and application examples of the library, hoping to make it widely known and get various feedbacks on this developing project.

The following URLs provide demos and details of the project.