Current software and platforms used in design-centric industries like AEC (architecture, engineering, construction) often take a 'data-first' approach where data type and structure dictate their visualization. Maintaining the fidelity of data in designing visualisations is important, but visualisations used for decision making in design-centric industries like AEC (architecture, engineering, construction) should focus on generating actionable insight.

This project investigated the development of a ‘decision-making first’ framework for creating data visualisations for design data, drawing from human-computer interaction research and our own experiments to develop data visualisation tools for designers. I designed and implemented experiments that investigated factors such as chart type, the number of options and dimensions shown, had on the quality of a decision made on behalf of someone else. Concurrently, I also developed data visualization frameworks in Vue and Svelte based on Bertin’s Grammar of Graphics (now released as Florence) and taught classes on interactive data visualization for beginners. Based on our findings and existing literature, I developed the visualization recommendation system for a web-based tool that visualizes design data with large amounts of options and dimensions.