Visual Analytics of Music

Theoretical (Analytical):

Practical (Implementation):

Literature Work:


  • Analyzing patterns in music and finding similar music compositions is a complex issue and provides a wide area of research with a growing community.
  • Understanding musical features such as harmony, rhythm, and structure is a difficult task
  • The target is to develop new interactive visual analysis techniques that support the analysis of relevant features in music data based on MusicXML
  • Implementation of user-steered analysis methods based on new visualizations to identify musical patterns of and between different features

Problem Statement

  • How can we visualize musical features?
  • How can interactive analysis techniques be implemented to identify characteristic musical patterns?


  • Examine and identify existing approaches and analysis models
  • Work with a large dataset of music data based on the established MusicXML standard format
  • Implement a visualization pipeline that processes and transforms raw MusicXML files into interactive visualization models
  • Create analysis models that support that understanding of pattern from different musical features


  • Interest in learning about music and its underlying theory (e.g., harmony, rhythm, structure)
  • Basic knowledge about information visualization
  • Good programming skills in Python or Java (for backend) and web programming skills (HTML / JavaScript / D3)
  • Readiness to do creative research work independently


  • Scope: Bachelor / Master
  • Project/Thesis Duration: 3 months / 3 months (Bachelor), 3 months / 6 months (Master)
  • Start: immediately



  • M. Good. MusicXML for notation and analysis. The virtual score: representation, retrieval, restoration 12:113-124, 2001.
  • W. Chan, and Qu Huamin. A Report on Musical Structure Visualization. Leonardo, Department of Computer Science and Engineering Hong Kong University of Science and Technology Clear Water Bay, Kowloon, Hong Kong, 2007.
  • T. Bergstrom, K. Karahalios, and J. C. Hart. Isochords: visualizing structure in music. In Proceedings of Graphics Interface 2007. ACM, 2007.