Thema| A software framework for the quantitative study of compositional process

<p> There is a small but growing body of research addressing compositional process. The majority of this research is qualitative in nature. Due to the nature of the data collected as well as the means of its analysis, it is difficult to pursue this research at scale. What quantitative research...

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Bibliographic Details
Main Author: McCulloch, Peter
Language:EN
Published: New York University 2014
Subjects:
Online Access:http://pqdtopen.proquest.com/#viewpdf?dispub=3643034
Description
Summary:<p> There is a small but growing body of research addressing compositional process. The majority of this research is qualitative in nature. Due to the nature of the data collected as well as the means of its analysis, it is difficult to pursue this research at scale. What quantitative research does exist is limited in scope due to a lack of effective data collection tools. </p><p> To address these concerns a custom piece of notation software, <i> Thema,</i> was created. <i>Thema</i> automatically tracks composers' actions within the software environment and stores the date in a MySQL database; the database is integrated into the program and plays an active role in its operations. Entities in the score, such as notes, measures, and dynamics, are tracked across time using permanent identifiers. <i>Thema </i> also records the state of the notation environment as the composer works including viewable area, selections in the score, playback, and continuous MIDI keyboard input. Additionally, <i>Thema</i> records a screen capture for every action performed in the program. </p><p> This document describes the architecture and implementation of <i> Thema</i> as well as its usage in a study of ten graduate-level composers. To examine the study's data, a custom suite of visualizations, <i>Omaggio, </i> was created. Using these visualizations, the development of musical structure over time is investigated in detail; a case study of local problem-solving behavior in the context of improvisational and score data is also presented. This work has implications for compositional process research, composition pedagogy and musicology, and illustrates the power of combining automatic data collection with a rich data model. This new method of data collection is non-intrusive, anonymous, and practical for regular use by composers. The analytic tools presented herein integrate keyboard and score data and could be helpful to composers during the process of composition. Additionally, these tools could serve a role in future qualitative studies by reducing organizational overhead and providing search capabilities. To facilitate further research, the musical works from the study are released under a Creative Commons license and the compositional process data set will be accessible to researchers. </p>