A quiet study of
public music metadata.
An independent, non-commercial research project exploring patterns, tempo distributions, and engagement signals across publicly available track metadata.
OpenSound Lab is a personal learning initiative investigating how musical characteristics — tempo, duration, genre, engagement — distribute across publicly shared tracks on open audio platforms.
The project is built as a sandbox for practicing data analysis, visualization, and metadata science techniques on real-world cultural data. All findings are derived from publicly available information, studied in aggregate, and published openly for educational discussion.
There is no commercial product, no client deliverable, and no monetization path. The work exists as portfolio and practice.
Four questions the lab is quietly asking.
Tempo Geography
How do BPM distributions vary across genres? Are certain tempos culturally tied to specific styles?
Duration Patterns
How has average track length shifted? Which genres prefer brevity and which embrace length?
Engagement Signals
What is the observable relationship between play counts, likes, and comment activity across the corpus?
Genre Topology
How do tagged genres cluster and overlap? Where do the boundaries between neighboring genres dissolve?
The process is deliberately small.
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01Sample publicly listed tracks using documented API search parameters. Search fields: genre tags, BPM range, duration range, access type.
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02Collect only public metadata — titles, tags, BPM, duration, engagement counts. No audio content is downloaded, stored, or redistributed.
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03Analyze distributions, correlations, and clusters using Python & standard statistical tooling. Results are always expressed as aggregate trends, never as individual track claims.
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04Publish findings as open notebooks and written notes with full attribution. Any embedded examples link back to the original track via official players.
What this project is, and is not.
- Public metadata analysis
- Aggregate pattern study
- Educational notebooks
- Open attribution practice
- Personal skill development
- Audio downloading or storage
- Content redistribution
- Commercial services
- User-facing products
- Any monetization