Sonification and journalism: how to play data through sounds

• Autores: Rodríguez Mateos, David, Tapia López, Alicia
• Formato: artículo
• Fecha de Publicación: 2023
• Institución: Universidad de Piura
• Repositorio: Revista de Comunicación
• Lenguaje: español
• OAI Identifier: oai:revistas.udep.edu.pe:article/3022
• Enlace del recurso: https://revistadecomunicacion.com/article/view/3022
• Nivel de acceso: acceso abierto
• Materia: sonificación; periodismo; datos; sonido; ciencia; discapacidad visual; activismo; audificación; software; emotividad; sonification; journalism; data; sound; science; visually impaired people; activism; audification; emotiveness

Sonification is a technique for representing data using sound, which has been used in various disciplines, including journalism, more intensively in the last 40 years. Its use with journalistic content is closely linked to practices in other fields, such as the representation of large scientific volumes of data, as well as the interpretation of data sets through sounds for visually impaired people. This article aims to provide a theoretical approach to sonification, an overview of its evolution and the challenges of its use in the context of news reporting. It includes a general introduction to sonification, its main elements and techniques, as well as a bibliographical analysis of both academic and professional literature. As a result, an overview of work based on sonifications is presented: firstly, applied to scientific productions and to people with visual impairment. Based on the above, specific examples of journalistic sonifications are presented, as well as descriptions of tools used to develop this technique. Sonification has proved useful as an alternative representation for discriminating differences in large volumes of data. However, much of its output and tools are still experimental. The complexity of human perception of sound, the difficulty of balancing its emotive and informative values, and the need to train the public in the use of this technique mean that it has yet to become a mass form of data representation.