Reflecting on qualitative and quantitative data to frame criteria for effective sonification design

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Abstract

A subjective stagnation in the field of sonification research has been discussed. However, sonification has spread in simpler forms. We present a data set from Google scholar that provides insights into the state of sonification research. Based on these data, the literature, and a small expert poll, we propose criteria for effective sonification design: the use of easily perceptible sounds, that are mapped naturally, do not contradict the data metaphor, and are appropriate to the task. A quantitative analysis of the data found no correlation between effective sonifications and the number of citations or the year of their publishing.

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Groß-Vogt, K., Enge, K., & Zmölnig, Io. M. (2023). Reflecting on qualitative and quantitative data to frame criteria for effective sonification design. In ACM International Conference Proceeding Series (pp. 93–100). Association for Computing Machinery. https://doi.org/10.1145/3616195.3616233

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