README.md

---
license: cc-by-4.0
task_categories:
# - music-information-retrieval
# - symbolic-music
- audio-classification
- audio-to-audio
tags:
- midi
- music
- audio-features
- million-song-dataset
- data-vault
configs:
  - config_name: mart_artist_profile_sample
    data_files:
      - "gold_lakh_midi/mart_artist_profile_sample.parquet"
  - config_name: mart_track_analytics_sample
    data_files:
      - "gold_lakh_midi/mart_track_analytics_sample.parquet"
  - config_name: mart_musical_features_sample
    data_files:
      - "gold_lakh_midi/mart_musical_features_sample.parquet"
  - config_name: hub_artist
    data_files:
      - "silver_lakh_midi/hub_artist.parquet"
  - config_name: hub_key_signature
    data_files:
      - "silver_lakh_midi/hub_key_signature.parquet"
  - config_name: hub_midi_file
    data_files:
      - "silver_lakh_midi/hub_midi_file.parquet"
  - config_name: hub_midi_source
    data_files:
      - "silver_lakh_midi/hub_midi_source.parquet"
  - config_name: hub_mode
    data_files:
      - "silver_lakh_midi/hub_mode.parquet"
  - config_name: hub_release
    data_files:
      - "silver_lakh_midi/hub_release.parquet"
  - config_name: hub_track
    data_files:
      - "silver_lakh_midi/hub_track.parquet"
  - config_name: link_artist_similar
    data_files:
      - "silver_lakh_midi/link_artist_similar.parquet"
  - config_name: link_midi_source
    data_files:
      - "silver_lakh_midi/link_midi_source.parquet"
  - config_name: link_track_artist
    data_files:
      - "silver_lakh_midi/link_track_artist.parquet"
  - config_name: link_track_midi
    data_files:
      - "silver_lakh_midi/link_track_midi.parquet"
  - config_name: link_track_release
    data_files:
      - "silver_lakh_midi/link_track_release.parquet"
  - config_name: sat_artist
    data_files:
      - "silver_lakh_midi/sat_artist.parquet"
  - config_name: sat_artist_mbtags
    data_files:
      - "silver_lakh_midi/sat_artist_mbtags.parquet"
  - config_name: sat_artist_similarity
    data_files:
      - "silver_lakh_midi/sat_artist_similarity.parquet"
  - config_name: sat_artist_terms
    data_files:
      - "silver_lakh_midi/sat_artist_terms.parquet"
  - config_name: sat_key_signature
    data_files:
      - "silver_lakh_midi/sat_key_signature.parquet"
  - config_name: sat_match_scores
    data_files:
      - "silver_lakh_midi/sat_match_scores.parquet"
  - config_name: sat_midi_file
    data_files:
      - "silver_lakh_midi/sat_midi_file/**/*.parquet"
  - config_name: sat_mode
    data_files:
      - "silver_lakh_midi/sat_mode.parquet"
  - config_name: sat_release
    data_files:
      - "silver_lakh_midi/sat_release.parquet"
  - config_name: sat_track
    data_files:
      - "silver_lakh_midi/sat_track/**/*.parquet"
size_categories:
- 100K<n<1M
---

# NTRC Lakh MIDI Dataset

> [!NOTE]  
> Check out the tables prefixed with `mart_*` to get started for some easy to understand and interesting data

This dataset contains an opionated, structured and lightly cleaned release of the [Lakh MIDI Dataset](https://colinraffel.com/projects/lmd/) by Colin Raffel, transformed using modern data engineering practices into a Data Vault 2.0 model.

## Dataset Description

The original Lakh MIDI Dataset is a collection of 176,581 unique MIDI files, 45,129 of which have been matched and aligned to entries in the Million Song Dataset. This processed version transforms the raw data into a structured format suitable for music information retrieval research and analysis.

**Key ideas in this release:**
- **Structured Data Vault 2.0 model** with hubs, links, and satellites
- **Bronze layer** with raw extracted data in Parquet format (not part of this distribution, see https://github.com/Nintorac/lakh_midi_dataset to build it)
- **Silver layer** with cleaned, deduplicated, and structured data
- **Gold layer** with clean derormalized views ready for ML pipelines and other downstream usecases

## Usage Examples

### Connecting to the Remote Database

You can attach to the remote Lakh MIDI database using DuckDB and query the processed data directly:

```sql
-- Attach the remote database
ATTACH 'hf://datasets/nintorac/ntrc_lakh_midi/lakh_remote.duckdb' AS lakh_remote;

-- Sample the artist profile mart table
CREATE TABLE my_artist_sample AS 
SELECT * FROM lakh_remote.mart_artist_profile 
WHERE artist_profile_tier = 'High Profile' 
LIMIT 100;


-- Query the sample
SELECT 
    artist_name,
    total_tracks,
    avg_tempo,
    most_common_key,
    top_terms[1:3] as top_3_terms
FROM my_artist_sample
ORDER BY total_tracks DESC;
```

This approach allows you to fetch data from the gold layer, without having to manage the full silver layer locally. It's pretty slow though so it would be best to follow the above pattern to save a table locally before running analysis.

## Data Structure

To understand the schema of the silver layer check out the [schema_silver.dbml](https://github.com/Nintorac/lakh_midi_dataset/blob/main/schema_silver.dbml) - load it in [dbdiagram.io](https://dbdiagram.io/d) for an interactive view.

Below is a high level overview of how the tables fit together.

![high level silver schema diagram](assets/ntrc_lakh_schema_silver.png)

### Silver Layer (`silver_lakh_midi/`)
Structured using Data Vault 2.0 methodology:

#### Hubs (Business Entities)
- **`hub_track.parquet`** - MusicBrainz tracks
- **`hub_artist.parquet`** - Artists (including similar artists)
- **`hub_release.parquet`** - 7digital releases  
- **`hub_midi_file.parquet`** - MIDI files by MD5 hash
- **`hub_midi_source.parquet`** - Source file paths
- **`hub_key_signature.parquet`** - Musical key signatures (0-11)
- **`hub_mode.parquet`** - Musical modes (0=minor, 1=major)

#### Links (Relationships)
- **`link_track_midi.parquet`** - Track-to-MIDI matches
- **`link_track_artist.parquet`** - Track-to-artist relationships
- **`link_track_release.parquet`** - Track-to-release relationships
- **`link_artist_similar.parquet`** - Artist similarity relationships
- **`link_midi_source.parquet`** - MIDI-to-source path mappings

#### Satellites (Descriptive Data)
- **`sat_track/`** - Track details, audio analysis, and time-series arrays (partitioned)
- **`sat_artist.parquet`** - Artist metadata and location info
- **`sat_release.parquet`** - Release information
- **`sat_midi_file/`** - MIDI file content and size (partitioned)
- **`sat_match_scores.parquet`** - Match quality scores
- **`sat_artist_similarity.parquet`** - Similarity rankings
- **`sat_artist_terms.parquet`** - Echo Nest artist terms
- **`sat_artist_mbtags.parquet`** - MusicBrainz tags
- **`sat_key_signature.parquet`** - Human-readable key signature names
- **`sat_mode.parquet`** - Human-readable mode names

## Data Quality Features

- **Deduplication**: Consistent handling of duplicate entities
- **Referential Integrity**: All foreign keys reference valid parents
- **Partitioned Storage**: Large tables partitioned by hash key prefix for scalable processing
- **Comprehensive Testing**: Data quality tests ensure consistency and completeness

## Technical Details

- **Format**: Apache Parquet with snappy compression
- **Schema**: Data Vault 2.0 with hash keys for scalable joins
- **Processing**: Built with dlt, dbt, and DuckDB
- **Partitioning**: Large tables partitioned by first character of hash keys (0-9, a-f)

## Original Dataset Information

This processed dataset is based on the Lakh MIDI Dataset, which contains:
- **176,581 unique MIDI files** from LMD-full
- **45,129 matched files** aligned to Million Song Dataset entries
- **Audio analysis features** from Echo Nest
- **Artist metadata** including MusicBrainz tags and similarity data

## Citations & License

### License
This dataset is distributed under the [CC-BY 4.0](http://creativecommons.org/licenses/by/4.0/) license, following the original Lakh MIDI Dataset license.

### Required Citations

If you use this dataset, please cite the original Lakh MIDI Dataset:

```bibtex
@phdthesis{raffel2016learning,
  title={Learning-Based Methods for Comparing Sequences, with Applications to Audio-to-MIDI Alignment and Matching},
  author={Raffel, Colin},
  year={2016},
  school={Columbia University}
}
```

For the Million Song Dataset metadata, please also cite:

```bibtex
@inproceedings{bertin2011million,
  title={The Million Song Dataset},
  author={Bertin-Mahieux, Thierry and Ellis, Daniel PW and Whitman, Brian and Lamere, Paul},
  booktitle={Proceedings of the 12th International Society for Music Information Retrieval Conference},
  pages={591--596},
  year={2011}
}
```

### Attribution Note

The original MIDI files were scraped from publicly-available sources on the internet and de-duplicated by Colin Raffel. While MIDI files have a built-in mechanism for attribution (the Copyright meta-event), it is not used consistently, so attributing each individual MIDI file to a particular author is not feasible.

## Processing Pipeline

This dataset was processed using:
- **dlt** for data extraction from unstructured files
- **dbt** for data transformation and testing
- **DuckDB** as the analytics database engine
- **Data Vault 2.0 methodology** for scalable data modeling

For more information about the processing pipeline, see the [project repository](https://github.com/nintorac/lakh_midi_dataset).

## Resources

- [Colin Raffel's project page](https://colinraffel.com/projects/lmd/).
- [Million Song Dataset](http://millionsongdataset.com/)
- [Echo Nest Schema](https://developer.spotify.com/documentation/web-api/reference/get-audio-analysis)