Computational Network Semantics and Critical Properties of Music Notation Datasets

Abstract This article describes the semantics of notation systems for music as a network of transformations that connects the syntactic elements of the notation on one side and the semantic meaning, such as the parameters of a possible execution, on the other side. In this context, a digital encoding format for music notation can be defined by selecting a subset of the data nodes of this network for storage, leaving others to evaluation. We discuss how to integrate uncertainty, freedom of choice, and graphical attributes, and we give semantic properties of datasets that impact upon the practical costs of maintenance, migration, and extension, among other things. For their demonstration and evaluation, these dataset properties are applied to selected substrata of four widely used encoding systems: MIDI Standard File, LilyPond, MusicXML, and Music Encoding Initiative.