DSW 2019 - DATASET SHOWCASE WORKSHOP

MusicOSet - An Enhanced Music Dataset for Music Data Mining

Dataset Information

This repository stores an open and enhanced dataset of musical elements (music, albums, and artists) suitable for music data mining.

The attractive features of MusicOSet include:

• Integration and centralization of different musical data sources
• Calculation of popularity scores and classification of hits and non-hits musical elements, varying from 1962 to 2018
• Enriched metadata for music, artists, and albums from the US popular music industry
• Availability of acoustic and lyrical resources
• Unrestricted access in two formats: SQL database and compressed .csv files

Dataset Statistics

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Data	# Records
Songs	20,405
Artists	11,518
Albums	26,522
Lyrics	19,664
Acoustic Features	20,405
Genres	1,561

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Schema

Format and Usage

MusicOSet is available in a public repository in two different formats

1. Relational Database
   • musicoset.sql: SQL file that will create the relational database and subsequently loads all the information in the tables by a MySQL installation (233MB)
2. .csv Tables
   • musicoset_metadata.zip: Contains textual and numeric information about songs, artists, and albums (5,73MB)
   • musicoset_popularity.zip: Contains nine tables of musical popularity information (11,8MB)
   • musicoset_songfeatures.zip: Contains lyrics and acoustic fingerprints of the songs collected (52MB)

Applicability

• Metadata Analysis: Collaboration profiles and their impact on musical success, ACM/SAC, Cyprus, 2019.
• Hit Song Science: Causality analysis between collaboration profiles and musical success, Technical Report, Brazil, 2019.

Source (citation)

@InProceedings{silva2019musicoset,
title     = {{MusicOSet: An Enhanced Open Dataset for Music Data Mining}},
author    = {Silva, Mariana O. and Rocha, La\'{\i}s M. and Moro, Mirella M.},
booktitle = {{XXXIV} Simp{\'{o}}sio Brasileiro de Banco de Dados: Dataset Showcase Workshop, {SBBD} 2019 Companion},
address   = {Fortaleza, CE, Brazil},
year      = {2019}
}

License

• The dataset is meant for research purposes.

Acknowledgments

The work is supported by CNPq, Brazil.