Realism and selectivity in data-driven visualisations: A process for developing viewer-oriented landscape surrogates

Abstract While data-driven visualisations are often intended to provide a realistic surrogate for actual environments, the necessary selection of landscape elements to include or exclude raises complex psychological, ethical and technical issues. This paper describes a process, based on social research, for prioritising landscape elements for inclusion in visualisations. It is argued that development of visualisations should draw on qualitative and quantitative social research to identify landscape elements most important to participants’ landscape assessments, and should involve diverse participants that match intended end-users.