Air pollution is currently a hot topic and a significant threat that impacts not only climate change but also the health of individuals. As a matter of fact, it was estimated that it causes 6.7 million premature deaths annually, and, in 2021, 97% of the urban population was exposed to particulate matter concentrations above the World Health Organization’s health-based guideline. Generally, individuals have no perception of the air quality around them and in the city where they live, and their knowledge of the subject depends on what they learn from newscasts or newspapers. However, increasing awareness of the topic can help them make more conscious choices. To partly tackle this problem, we developed a web-based prototype exploiting two modalities to communicate air quality data: data sonification (through audio) and data visualization (through animated video). With the aim of investigating the best communication modality that, eventually, can raise awareness on the topic, we performed a preliminary study. To anticipate some findings, we found out that the videos were considered less mentally demanding and less frustrating, while the sound was considered more pleasant. At the same time, while the videos required less time to be understood and communicated a more precise level of pollution, the audios were considered, on hand, more involving, making the users also feel more immersed in the experience, and, on the other hand, gave the possibility to concentrate on something else while experiencing the data.

What Does Air Quality Sound Like? On Exploring the impact of Data Sonification Versus Data Visualization / Ceccarini, Chiara; Tumedei, Gianni; Prandi, Catia. - ELETTRONICO. - (2023), pp. 510-516. (Intervento presentato al convegno 3rd ACM Conference on Information Technology for Social Good tenutosi a Lisbon nel 6 - 8 September 2023) [10.1145/3582515.3609575].

What Does Air Quality Sound Like? On Exploring the impact of Data Sonification Versus Data Visualization

Ceccarini, Chiara
;
Tumedei, Gianni;Prandi, Catia
2023

Abstract

Air pollution is currently a hot topic and a significant threat that impacts not only climate change but also the health of individuals. As a matter of fact, it was estimated that it causes 6.7 million premature deaths annually, and, in 2021, 97% of the urban population was exposed to particulate matter concentrations above the World Health Organization’s health-based guideline. Generally, individuals have no perception of the air quality around them and in the city where they live, and their knowledge of the subject depends on what they learn from newscasts or newspapers. However, increasing awareness of the topic can help them make more conscious choices. To partly tackle this problem, we developed a web-based prototype exploiting two modalities to communicate air quality data: data sonification (through audio) and data visualization (through animated video). With the aim of investigating the best communication modality that, eventually, can raise awareness on the topic, we performed a preliminary study. To anticipate some findings, we found out that the videos were considered less mentally demanding and less frustrating, while the sound was considered more pleasant. At the same time, while the videos required less time to be understood and communicated a more precise level of pollution, the audios were considered, on hand, more involving, making the users also feel more immersed in the experience, and, on the other hand, gave the possibility to concentrate on something else while experiencing the data.
2023
Proceedings of the 2023 ACM Conference on Information Technology for Social Good
510
516
What Does Air Quality Sound Like? On Exploring the impact of Data Sonification Versus Data Visualization / Ceccarini, Chiara; Tumedei, Gianni; Prandi, Catia. - ELETTRONICO. - (2023), pp. 510-516. (Intervento presentato al convegno 3rd ACM Conference on Information Technology for Social Good tenutosi a Lisbon nel 6 - 8 September 2023) [10.1145/3582515.3609575].
Ceccarini, Chiara; Tumedei, Gianni; Prandi, Catia
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/953921
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