Translating NASA moon crater data into sound and motion — an exploration of how sonification can enhance perception of scientific data.
This project maps physical properties of lunar craters to audio and visual parameters, creating an interactive experience that reveals patterns in NASA's crater database through multiple sensory channels.
Parameter Mapping:
- Crater diameter → pitch (inverted: larger = lower, 110–330 Hz) + duration
- Latitude/longitude → impact position
- Volume scaled to crater size
| File | Description |
|---|---|
open-space-sonification-3.html |
Interactive visualization and case study |
OpenSpaceNotebook.ipynb |
Python data processing and MIDI generation |
moon_craters_small_20.csv |
Source data from NASA Moon Crater Database |
| `SonProjectMoon2.mid' | MIDI File output |
OpenSpaceAudio.mp3 |
Logic Pro composition from MIDI output |
sketch1.2.png, sketch1.3.png, sketch1.10.png |
Data analysis visualizations |
- Data Processing: Python, NumPy, Pandas, Matplotlib
- MIDI Generation: midiutil
- Audio Production: Logic Pro
- Visualization: JavaScript, Web Audio API, HTML5 Canvas
- AI Collaboration: Claude, Grok (code structure, iteration)
During development, I identified pitch values that weren't correctly correlated with crater sizes. AI-generated code required human verification to ensure perceptual accuracy. This iterative process highlighted complementary strengths: AI excels at code structure and math; human perception catches relationship inconsistencies.
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Petra Kühnle
MIT