2026/27 Taught Postgraduate Module Catalogue

MUS5113M Music Data Research

30 Credits Class Size: 20

Module manager: Professor Bryan White
Email: b.white@leeds.ac.uk

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2026/27

This module is not approved as an Elective

Module summary

In this module you will explore the use of music data sets as a tool of research in the field of music studies. Large data sets can inform the investigation of music publishing, concert going and advertising, changes in musical genre and other historical trends in music production, distribution and consumption. Using music data sets requires an understanding of how data sets can be collected and exploited, the affordances and challenges of metadata, and modes of data set analysis, presentation and visualisation. Through case studies you will examine precedents for the use of data sets in music research. You will identify potential data sets and the purposes for which they may be used and propose strategies for carrying out research on such data sets within an ethical framework.

Objectives

The aim of this module is to develop your understanding of the use of data sets as research tools in the field of music studies The objectives of the module are to:

- Explore case studies in which data sets are used to answer research questions in music studies
- Evaluate music data sets for their structure and metadata protocols
- Explore different tools for analysing music data
- Develop ways of presenting insights from music data analysis
- Consider the ethical implications of the use of music data sets

Learning outcomes

On successful completion of the module students will be able to:

1) Apply methodologies for the analysis of music data sets
2) Evaluate data sets for their quality and consistency
3) Manipulate data sets for the purposes of music research
4) Evaluate the ethical implications of the use of music data sets in research projects
5) Communicate using a variety of modes of presenting insights generated through the analysis of data sets

Teaching Methods

Delivery type Number Length hours Student hours
Supervision 2 0.5 1
Lecture 5 2 10
Seminar 3 2 6
Private study hours 283
Total Contact hours 17
Total hours (100hr per 10 credits) 300

Opportunities for Formative Feedback

Formative feedback takes place in seminars and through feedback on a project outline proposal Formative feedback will be offered in seminars in which students experiment with the use of data sets. In tutorials students will receive feedback on work in progress on their project.

Methods of Assessment

Coursework
Assessment type Notes % of formal assessment
Coursework Project 100
Total percentage (Assessment Coursework) 100

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading List

Check the module area in Minerva for your reading list

Last updated: 06/03/2026

Errors, omissions, failed links etc should be notified to the Catalogue Team