improve model card documentation

.gitattributes

@@ -1,3 +1,3 @@
 **/*.parquet filter=lfs diff=lfs merge=lfs -text
 *.duckdb filter=lfs diff=lfs merge=lfs -text
-lakh_local.duckdb filter=lfs diff=lfs merge=lfs -text
+assets/* filter=lfs diff=lfs merge=lfs -text

README.md

@@ -12,12 +12,12 @@ tags:
 - million-song-dataset
 - data-vault
 configs:
-  - config_name: mart_track_analytics_sample
-    data_files:
-      - "gold_lakh_midi/mart_track_analytics_sample.parquet"
   - 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"
@@ -91,24 +91,61 @@ size_categories:
 - 100K<n<1M
 ---
 
-# Processed Lakh MIDI Dataset
+# 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 a structured, processed version 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.
+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 improvements in this processed version:**
+**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 distributed, see https://github.com/Nintorac/lakh_midi_dataset to build it)
+- **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:
 
@@ -140,36 +177,6 @@ Structured using Data Vault 2.0 methodology:
 - **`sat_key_signature.parquet`** - Human-readable key signature names
 - **`sat_mode.parquet`** - Human-readable mode names
 
-## 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.
-
 ## Data Quality Features
 
 - **Deduplication**: Consistent handling of duplicate entities
@@ -234,8 +241,10 @@ This dataset was processed using:
 - **DuckDB** as the analytics database engine
 - **Data Vault 2.0 methodology** for scalable data modeling
 
-For more information about the processing pipeline, see the [original project repository](https://github.com/nintorac/lakh_midi_dataset).
+For more information about the processing pipeline, see the [project repository](https://github.com/nintorac/lakh_midi_dataset).
 
-## Contact
+## Resources
 
-For questions about this processed version of the dataset, please refer to the original project repository. For questions about the original Lakh MIDI Dataset, please refer to [Colin Raffel's project page](https://colinraffel.com/projects/lmd/).
+- [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)