Modeling, exploring and recommending music in its complexity

Knowledge models that are currently in-use for describing music metadata are insufficient to express the wealth of complex information about creative works, expressions, performances, publications, authors and performers. In this research, we aim to propose a method for structuring the classical music information coming from different heterogeneous librarian repositories. In particular, we research and implement an appropriate music ontology based on existing models, controlled vocabularies and tools for converting and visualizing the metadata. Moreover, we research how this data can be consumed by end-users, through the development of a web application for exploring the data and a recommendation system that takes advantage of the richness of the data.