Aural

Data sonification is a practice and genre in which numerical or categorical datasets are mapped to sound so that patterns in the data are perceived as musical structure. It differs from simple parameter automation by letting the data itself determine pitch, rhythm, dynamics, timbre, and spatial behavior through clearly defined mappings. Works range from direct audification of scientific signals (e.g., seismic or astronomical measurements) to carefully designed parameter mappings and model-based approaches that translate complex, multivariate datasets into layered sonic textures. Because it sits at the intersection of art, science, and design, data sonification is used both for aesthetic expression and for communicating or revealing structure in data that might be hard to see visually.