Charts turn data into visual images that make information more visible and interpretable. But another way to share data is to turn numbers into sound, for example to find new patterns in data, make it more accessible or just more engaging. Researchers recently studied a group of volunteers who listened to weather data as sounds to discover how different interpretations of the data as sound changed people’s listening experience.
Data recording is the process of converting data into sound patterns. There are several ways to do this. It can be as simple as a series of beeps and clicks or as elaborate as a fully orchestrated symphony. But what kind of sound would be more appealing to listen to? To find out, researchers in Finland and the US investigated how people responded to different data recording methods.
Any data can be recorded, but for this study used data from Finnish weather records. The data was converted into three sets of sounds: one where the data was represented as a melody, one where it was converted into chords, and the last as a beat. Within each set, the audio data were presented as a simple sound, a sound with added timbre, or a more complex sound with added color and rhythm. So in total, there were nine possible sounds to listen to.
The volunteers were given some of these sounds in random order and asked to rate certain statements about it, such as “I was absorbed in my listening task” and “the content of the sounds piqued my curiosity.”
After analyzing all the data, the researchers found some small differences in how people felt about the different sounds. For example, when the data was presented as a beat, people were more focused listening to simple sounds than to more complex sounds. But if they heard data translated into melodies, they found the sound more pleasant if it had complex overtones.
Why does it matter how people perceive data sounds? “In a digital world where the collection and interpretation of data has become integrated into our daily lives, researchers are proposing new perspectives on the experience of performance,” said Jonathan Middleton, professor of music theory and composition at Eastern Washington University and lead researcher on the study. . he said at the University of Tampere (where he is a visiting researcher). “Since musical sounds can be particularly appealing, this research offers new opportunities to understand and interpret data as well through our auditory senses,” he adds.
There are several reasons why one might convert data to audio. Some people may use data recording as a creative way to draw attention to data. For example, Jamie Perera came back climate data in an agreement. Another purpose for recording data is to find new information in the data. Astronomers can point anomalies in noise-processed telescope data which would be hidden in visual images. And finally, audioization can be a way to make research data more accessible to people who cannot get the information from visual representations. There is a project called Accessible oceans which converts ocean data into sound for this purpose.
Because there are several reasons for using recording data, it’s good to know how these sounds affect the listener’s experience. If sound is used to hear patterns, for example, it might make sense to have a type of sound that keeps people focused. But if intended as art or display, an aesthetically pleasing genre of music may work best.
Charts aren’t going anywhere, of course, and remain a good way to get a quick overview of data patterns at a glance. But by turning data into sound, it can be shared in new ways with more people. And understanding what makes this sound appealing will be helpful to anyone with data to share.