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Toward a universal, meta-theoretical framework for music information classification and retrieval

Lynnsey Weissenberger (School of Library and Information Studies, Florida State University, Tallahassee, Florida, United States of America)

Journal of Documentation

ISSN: 0022-0418

Article publication date: 14 September 2015

1044

Abstract

Purpose

The purpose of this paper is to present a new framework for representing music for information retrieval that emphasizes socio-cultural aspects of music.

Design/methodology/approach

Philosophical and theoretical concepts related to the nature of music, aboutness, musical works are explored as they inform how music is represented. Multidisciplinary perspectives on music information representation, classification, and retrieval provide insight into how information science can better accommodate music information within its disciplinary boundaries.

Findings

A new term, music information object (MIO), is presented and defined. Downie’s (2003) theoretical statements are reconceptualized into a theory of representational incompleteness and three meta-classes for music information object representation.

Practical implications

This new framework incorporates more dimensions of music representation than existing frameworks allow and can facilitate comparisons between classifications of MIO representations by music practitioners, scholars, and system developers.

Originality/value

The meta-classes form a much-needed theoretical framework for classifying and defining MIOs from any musical tradition for retrieval. This fills a gap in music information retrieval research, which lacks a theoretical framework that can accommodate musics from all traditions without attempting to organize them according to a western-centered understanding.

Keywords

Acknowledgements

The author wishes to acknowledge the encouragement of Dr Corinne Jörgensen while pursuing this line of inquiry.

Citation

Weissenberger, L. (2015), "Toward a universal, meta-theoretical framework for music information classification and retrieval", Journal of Documentation, Vol. 71 No. 5, pp. 917-937. https://doi.org/10.1108/JD-08-2013-0106

Publisher

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Emerald Group Publishing Limited

Copyright © 2015, Emerald Group Publishing Limited

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