Explore our research!

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.

Augmenting Digital Sheet Music through Visual Analytics

Typically, music analysts use common music notation to analyze musical compositions. Diverse abstract visualization techniques have been published to address different music analysis task. Often they lack a suitable connection to the standard notation, which makes it difficult for analysts to combine close and distant reading. We introduce a visual analytics technique to augment the standard notation with abstract glyph visualization in a minimally instrusive way to combine close and distant reading for sheet music.

Framing Musicology through Methodology Transfer

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.

Augmenting Music Sheets with Harmonic Fingerprints

We use visualization and analysis of music data to enhance the harmonic analysis of sheet music. We investigate, how musicologists can profit from a visualization that is based on the circle-of-fifths to provide an intuitive understanding for domain experts. The harmonic fingerprint facilitates the identification of similar harmonies. By conducting a user study, we found that the fingerprint is invariant to the octave of the notes, since the chromatic scale is repeated at every octave.

Analyzing Visual Mappings of Traditional and Alternative Music Notation

Combining the domains of information visualization and music studies paves the ground for a more structured visual analysis of the design space of music notation, enabling the creation of alternative music notations that are tailored to different users and their tasks. We propose a design and visualization pipeline for music notation to conceptualize, create, analyze, and evaluate the effectiveness of novel music notation methods.

Meet our team!

Matthias Miller

Mennatallah El-Assady

Hanna Schäfer

Matthias Kraus