Accompanying files for the doctoral thesis ‘Parameter mapping sonification of biological data’ by Edward J. Martin

Algorithmic parameter mapping (PM) sonification is an innovative approach to scientific data representation using sound, with task-specific projects showing promise across a range of biological data for a range of purposes. This work develops a range of novel task-specific PM sonification algorithms for the representation of biological data. In Chapter 1, a sonification concert is presented, hosted in collaboration with other sonification researchers, showcasing works created using PM sonification of biological sequence data (nucleotides and amino acids) as a method of public engagement with molecular evolution. In Chapter 2, an approach to inspire action on biodiversity loss is presented, featuring a PM sonification method representing global biodiversity index data (Living Planet Index) by the soundwave-level deletion of data from familiar/recognisable audio. In Chapter 3, a proposed zoo installation engaging visitors with genomic research into the stewardship of endangered species through the example of the Mauritian pink pigeon (Nesoenas mayeri) in presented, featuring a PM sonification method of genomic analysis data representing the risk of deleterious mutations in potential offspring. In Chapter 4, an approach to digital biological education is presented, using a method integrating narrative scaffolding techniques, podcasting sound design, and the PM sonification of biological concepts. Overall, the work uses a range of innovations in sonification methods to create sound outputs of a high quality, borrowing techniques from music/radio production and sound design, including the editing of existing recordings, narrative scaffolding techniques, use of the MIDI protocol, and mixing and mastering via Digital Audio Workstations (DAWs). Design processes focus on the listening experience of end-users, centring the task-specific nature of PM sonification and emphasising intended use-cases and context at all stages in design. Varied ways of understanding sound and features of human psychoacoustics are used in the design of these approaches. To emphasise the shareability and longevity of the work, which is adaptable for future applications with both biological and non-biological data sets, the works utilises open-source software, publicly available code sharing repositories, and a modular implementation approach facilitating post hoc sound design. The evaluation of these methods is end-user-focussed, using a suite of techniques from social research methods to provide evidence of success and insight into the subjective experiences of listeners. These include positivist experiments to measure the success of users in task-completion, alongside asking experts and end-users to affirm or deny the success of the methods, and interpretivist investigations into listener experience through interviews, focus groups, and questionnaires, which are also compared to design intentions. Overall, the works shows that centring the purpose of the approach and the experience of listeners in data processing, mapping, sound design, and evaluation methods helps create successful PM sonification projects.