Valery Vermeulen

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.

Experimental music is an umbrella term for practices that prioritize exploration, process, and discovery over adherence to established genre norms. It embraces new sound sources, nonstandard tuning systems, indeterminacy and chance operations, graphic and open-form scores, extended techniques, and technology-led sound design (tape, electronics, computers, and live processing). Rather than a single style, it is a methodology and ethos: testing hypotheses about sound, structure, and performance, often blurring boundaries between composition, improvisation, sound art, and performance art. Listeners can expect unfamiliar timbres, unusual forms, and an emphasis on how music is made as much as the resulting sound.