Music Curation and Analytics ARTMED4038
- Academic Session: 2018-19
- School: School of Humanities
- Credits: 20
- Level: Level 4 (SCQF level 10)
- Typically Offered: Either Semester 1 or Semester 2
- Available to Visiting Students: Yes
- Available to Erasmus Students: Yes
This course will explore how scholars and practitioners use musical data, both in audio and notated formats. Students will be given the opportunity to develop skills in encoding, analysing, categorizing, and curating music recordings and notated music. These skills will be developed by encouraging an intimate understanding of the nature of different musical formats, an appreciation of their uses, and approaches to computational analyses of their electronic manifestations.
One one-hour lecture and one one-hour seminar or lab session per week. (write out for full semester)
Requirements of Entry
Available to all students fulfilling requirements for Honours entry into Digital Media and Information Studies, and by arrangement to visiting students or students of other Honours programmes who qualify under the University's 25% regulation.
Project Output Dataset: Students will have to complete an analytical project based on a digital dataset
Report: The dataset will be accompanied with a report of 2,500 words
Project Output Dataset 60%
Main Assessment In: April/May
Are reassessment opportunities available for all summative assessments? Not applicable for Honours courses
Reassessments are normally available for all courses, except those which contribute to the Honours classification. For non-Honours courses, students are offered reassessment in all or any of the components of assessment if the satisfactory (threshold) grade for the overall course is not achieved at the first attempt. This is normally grade D3 for undergraduate students and grade C3 for postgraduate students. Exceptionally it may not be possible to offer reassessment of some coursework items, in which case the mark achieved at the first attempt will be counted towards the final course grade. Any such exceptions for this course are described below.
This course will provide students with the opportunity to:
■ deliver an introduction to digital methodologies in music analysis and curation, and the ways music data is manifested and visualized;
■ explain and apply methods for analyzing digital audio data;
■ explore the principles and best practice of notated music encoding, such as using XML;
■ provide training in methods of encoded notated music analysis;
■ apply relevant and appropriate encoding and analytics.
Intended Learning Outcomes of Course
By the end of this course, students will be able to:
■ formulate relevant research questions for music data;
■ assess how encoding and computational analyses can help answer research questions about music data;
■ evaluate how digital manifestations can change the ways in which music is used and analysed;
■ judge the effectiveness of computational methodologies in music research;
■ design and apply an appropriate encoding to a musical score, such as XML;
■ identify and implement standards and best practices generally accepted by the research community;
■ develop, test, and justify methods to communicate research outcomes based on music data analyses.
Minimum Requirement for Award of Credits
Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.