We frame the field of Visual Musicology by providing an overview of well-established musicological sub-domains, corresponding tasks, open challenges, and research opportunities to foster collaborative, interdisciplinary research. We argue, that through methodology transfer established methods can be exploited to support musicological research. Finally, we point out open challenges, discuss research gaps, and highlight future research opportunities.
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Compared to music that is rather a field with a quite long history, data analysis and visualization is a very young branch in Computer Science. In this project, we want to investigate, how musicology can profit from modern techniques. To provide useful visual analysis methods or tools for musical applications, an in-depth knowledge of music theory and its applications is required to develop appropriate techniques that support domain experts in their work. Providing a foundation that bridges both fields is targeted to create new approaches that lead to the generation of more deep knowledge. Integrating the user or domain expert holds the potential to maximize the knowledge output by combining the computing power of nowadays technology and human's intuition, understanding and background knowledge that can seldom completely covered by simply gathering data.