A Tangible User Interface for Interactive Data Visualisation

Information visualisation (infovis) tools are integral for the analysis of large abstract data, where interactive processes are adopted to explore data, investigate hypotheses and detect patterns. New technologies exist beyond post-windows, icons, menus and pointing (WIMP), such as tangible user interfaces (TUIs). TUIs expand on the affordance of physical objects and surfaces to better exploit motor and perceptual abilities and allow for the direct manipulation of data. TUIs have rarely been studied in the field of infovis. The overall aim of this thesis is to design, develop and evaluate a TUI for infovis, using expression quantitative trait loci (eQTL) as a case study. The research began with eliciting eQTL analysis requirements that identified high- level tasks and themes for quantitative genetic and eQTL that were explored in a graphical prototype. The main contributions of this thesis are as follows. First, a rich set of interface design options for touch and an interactive surface with exclusively tangible objects were explored for the infovis case study. This work includes characterising touch and tangible interactions to understand how best to use them at various levels of metaphoric representation and embodiment. These design were then compared to identify a set of options for a TUI that exploits the advantages of touch and tangible interaction. Existing research shows computer vision commonly utilised as the TUI technology of choice. This thesis contributes a rigorous technical evaluation of another promising technology, micro-controllers and sensors, as well as computer vision. However the findings showed that some sensors used with micro-controllers are lacking in capability, so computer vision was adopted for the development of the TUI. The majority of TUIs for infovis are presented as technical developments or design case studies, but lack formal evaluation. The last contribution of this thesis is a quantitative and qualitative comparison of the TUI and touch UI for the infovis case study. Participants adopted more effective strategies to explore patterns and performed fewer unnecessary analyses with the TUI, which led to significantly faster performance. Contrary to common belief bimanual interactions were infrequently used for both interfaces, while epistemic actions were strongly promoted for the TUI and contributed to participants’ efficient exploration strategies.