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Sound training platform applied to astronomy

Natasha Bertaina Lucero, Johanna Casado, Beatriz García, Gonzalo Cayo

TL;DR

This work addresses the gap in training and accessibility for data sonification in astronomy by proposing a web-based, adaptive training platform built on Django with PostgreSQL, designed to integrate with existing sonification tools like sonoUno. It reviews prior user studies and tools, motivates the need for open, accessible web deployment, and outlines a development path including modular training blocks, progress tracking, and multisensory data interpretation. The platform aims to lower barriers to multisensory participation in astronomy education and research, enabling broader inclusion and engagement with sound-encoded cosmic data. The work sets the stage for scalable, adaptable training that can evolve with diverse sonification methods and education goals.

Abstract

The convergence between astronomy and data sonification represents a significant advancement in the approach and analysis of cosmic information. By surpassing the visual exclusivity in data analysis in astronomy, innovative projects have developed software that goes beyond visual representation, transforming data into auditory and tactile displays. However, it has been evidenced that this novel technique requires specialized training, particularly for audio format data. This work describes the initial development of a platform aimed at providing training for data analysis in astronomy through sonification. The integration of these tools in astronomical education and research opens new horizons, facilitating a more inclusive and multisensory participation in the exploration of space science.

Sound training platform applied to astronomy

TL;DR

This work addresses the gap in training and accessibility for data sonification in astronomy by proposing a web-based, adaptive training platform built on Django with PostgreSQL, designed to integrate with existing sonification tools like sonoUno. It reviews prior user studies and tools, motivates the need for open, accessible web deployment, and outlines a development path including modular training blocks, progress tracking, and multisensory data interpretation. The platform aims to lower barriers to multisensory participation in astronomy education and research, enabling broader inclusion and engagement with sound-encoded cosmic data. The work sets the stage for scalable, adaptable training that can evolve with diverse sonification methods and education goals.

Abstract

The convergence between astronomy and data sonification represents a significant advancement in the approach and analysis of cosmic information. By surpassing the visual exclusivity in data analysis in astronomy, innovative projects have developed software that goes beyond visual representation, transforming data into auditory and tactile displays. However, it has been evidenced that this novel technique requires specialized training, particularly for audio format data. This work describes the initial development of a platform aimed at providing training for data analysis in astronomy through sonification. The integration of these tools in astronomical education and research opens new horizons, facilitating a more inclusive and multisensory participation in the exploration of space science.
Paper Structure (5 sections, 4 figures)

This paper contains 5 sections, 4 figures.

Table of Contents

  1. Introduction
  2. Preevious works
  3. Methods and Tools
  4. Development
  5. Conclusion

Figures (4)

  • Figure 1: A. Image and sound display in the training designed with Psychopy. B. Question and options are displayed for the user to answer using the Arrow Key block of the keyboard.
  • Figure 2: Basic diagram of the design of the database, represented and used in Django models.
  • Figure 3: Training page, with the list corresponding to the beginner level.
  • Figure 4: Example of deployment of mathematical functions training: beginner level.