Visualising the Structure of 18th Century Operas: A Multidisciplinary Data Science Approach
Paula Muñoz-Lago, Nicola Usula, Emilia Parada‐Cabaleiro, Álvaro Torrente · 2020 24th International Conference Information Visualisation (IV) · 2020
Data visualisation is an effective strategy to communicate information. From a multidisciplinary perspective, applying this methodology (typical of computer science) to humanistic purposes (such as visualising musical, narrative and dramaturgical structure) has shown very promising results. Opera is a complex form of art, whose structure is strongly influenced by dramaturgical and musical aspects, both present in all operatic librettos. Although visualisation methods have been successfully applied in the understanding of music and narrative individually, a combined approach, aimed to jointly visualise both aspects together-by this enhancing opera comprehension-has not yet been developed. With this in mind, through a cooperative methodology of musicology and computer science disciplines, we carry out a data science project aimed to graphically represent the structure of 18thcentury operas' libretto structure. The presented approach, based on XML librettos from the Progetto Metastasio, automatically generates a comprehensive graphical representation of the opera structure, based upon musical and dramaturgical information. The schemes developed in this work show all the elements relevant to the 18thcentury opera structure, and graphically synthesise its complex shape, in order to encourage opera understanding across a large set of users, from general listeners to musicians and finally to musicologists.