The Sonic Representation of Mathematical Data

Charlie Cullen (Thesis), Dublin Institute of Technology

Document Type Theses, Ph.D


Conveying data and information using non-speech audio is an ever growing field of research. Existing work has been performed investigating Sonification and its applications, and this research seeks to build upon these ideas while also suggesting new areas of potential. In this research, initial work focused on the Sonification of DNA and RNA nucleotide base sequences for analysis. A case study was undertaken into the potential of rhythmic parsing of such data sequences, with test results indicating that a more effective method of representing data in a Sonification was required. Sonification of complex data such as DNA and RNA was found to require more verbose methods than pitch to parameter mappings, and so investigation was made into musical pattern Sonification. Existing low level pattern design methods were next evaluated in an experiment concerning the use of musical patterns to represent data. This experiment suggested that while a musical pattern may be made distinct, it does not necessarily follow that it is memorable. This experiment also suggested that concurrent pattern representation was difficult to process, and so improved methods were required. Improvements to pattern design were made with the introduction of contour icons, which allow detectable and memorable musical patterns to be designed using simple shapes. Testing showed contour icons to be significantly more effective than low level patterns in a Sonification, and as such form the basis of the novel contribution of this thesis. Improvements in concurrent representation were considered by the use of harmonic combination, a method of defining intersections in a data set as harmonies of a single common musical pattern. Significant improvements were observed over non-harmonic concurrent representation, although limitations were observed due to constraints in the number of combinations available using a specific value. Harmonic combination has potential for futher development, and is a novel contribution of this thesis. The organisation and grouping of data in a Sonification using rhythmic parsing was also investigated. Rhythmic parsing uses rest notes within a musical framework to define sub-groupings in a data Sonification. Tests showed rhythmic parsing significantly improved the comparison of values and intersections between groups in a data Sonification, and is another novel contribution of this thesis.