CorpusVis: Visual Analysis of Digital Sheet Music Collections

Manually investigating sheet music collections is challenging for music analysts due to the magnitude and complexity of underlying features, structures, and contextual information. However, applying sophisticated algorithmic methods would require advanced technical expertise that analysts do not nec...

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Veröffentlicht in:Computer graphics forum Jg. 41; H. 3; S. 283 - 294
Hauptverfasser: Miller, Matthias, Rauscher, Julius, Keim, Daniel A., El‐Assady, Mennatallah
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford Blackwell Publishing Ltd 01.06.2022
Schlagworte:
CCS Concepts
Document structure
Human‐centered computing → Visualization techniques
Information systems → Content analysis and feature selection
Music
Qualitative analysis
Visual analytics
Visualization systems and tools
ISSN:0167-7055, 1467-8659
Online-Zugang:Volltext
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Zusammenfassung:Manually investigating sheet music collections is challenging for music analysts due to the magnitude and complexity of underlying features, structures, and contextual information. However, applying sophisticated algorithmic methods would require advanced technical expertise that analysts do not necessarily have. Bridging this gap, we contribute CorpusVis, an interactive visual workspace, enabling scalable and multi‐faceted analysis. Our proposed visual analytics dashboard provides access to computational methods, generating varying perspectives on the same data. The proposed application uses metadata including composers, type, epoch, and low‐level features, such as pitch, melody, and rhythm. To evaluate our approach, we conducted a pair‐analytics study with nine participants. The qualitative results show that CorpusVis supports users in performing exploratory and confirmatory analysis, leading them to new insights and findings. In addition, based on three exemplary workflows, we demonstrate how to apply our approach to different tasks, such as exploring musical features or comparing composers.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.14540