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An e-Research approach to Web-scale music analysis.

David De Roure¹, Kevin R Page, Benjamin Fields

¹Oxford e-Research Centre, University of Oxford, Oxford, UK. david.deroure@oerc.ox.ac.uk

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences

|July 20, 2011

Summary

This study introduces an e-Research approach for musical analysis, creating a web-accessible corpus of music data. It utilizes Semantic Web technologies and algorithms to extract features, enabling enhanced music data curation and analysis.

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Area of Science:

Digital Humanities
Music Information Retrieval
Computational Musicology

Background:

Large-scale digital music archives offer new opportunities for musical analysis.
Existing resources lack a common framework for collaborative analysis and data sharing.
The need for robust methodologies and tools to manage and analyze extensive music datasets is growing.

Purpose of the Study:

To develop an e-Research infrastructure for creating a web-accessible corpus of musical analyses.
To establish a methodology and tooling for future contributions to the corpus.
To demonstrate the utility of Linked Data for music signal data curation and analysis.

Main Methods:

Adoption of an e-Research approach integrating scientific workflow and Semantic Web technologies.

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Development of algorithms and tools for extracting features from recorded music.

Implementation of a prototype system utilizing Linked Data for data correlation and result publication.

Main Results:

Creation of a web-accessible corpus of musical analyses in a common framework.
Demonstration of a prototype system showcasing Linked Data's utility in music data curation.
Establishment of a methodology and tooling for future data enrichment and analysis.

Conclusions:

The developed infrastructure facilitates enhanced curation and analysis of music signal data.
Linked Data proves effective in correlating music analysis results with various data sources.
This approach supports emerging e-Research practices for large-scale web-based research.