Librería de visualizaciones accesibles

Abstract

[en] As data visualization becomes increasingly ubiquitous across various fields, from data science to online information communication, it is crucial to ensure that these graphs are accessible to all individuals, including those with visual or motor impairments. Improving the accessibility of graphs not only aligns with ethical principles of inclusion but also expands the reach and utility of the presented information, benefiting a broader and more diverse audience. This project represents a significant advancement towards creating a more inclusive and equitable digital environment for everyone. The project involved the development of a data visualization library called Altair-Easeviz, with the primary goal of enhancing the accessibility of generated graphs. To achieve this, accessibility heuristics were integrated, and specific functionalities were implemented for individuals with visual or motor disabilities. The library complements Vega-Altair, using Python as the primary programming language. Familiar technologies were employed, and an agile methodology was followed for development, optimizing the available time and resources. Additionally, a demonstration website was created detailing each available graph type and providing interactive examples for users. The website was deployed automatically using the Render platform, simplifying the deployment process and ensuring accessibility across different platforms. Finally, the library was published on PyPI, and a repository was maintained on GitHub for anyone to contribute to and expand the library. This project represented a significant step towards creating accessible and understandable graphs for all users.