The tremendously increased availability and volume of data is reshaping how scientific investigation is executed, however, scientists still resort to conventional statistical analysis routines. Data-intensive investigations and analysis requires a new set of tools for the effective and robust generation and testing of hypotheses. Visualisation offers possibilities that can embrace the variety, uncertainty, and the multi-dimensionality within phenomena being investigated. This project aims to investigate the role and limitations of visual representations as scientific evidence to support and provide confidence within hypothesis generation and testing processes.
Review literature in statistical and visual data analysis to build an understanding on the use of visualisation as an inference methodology
Design visual representations to be used as evidence in supporting scientific arguments within data-intensive hypothesis generation and testing settings
Design studies to investigate the effectiveness of visualisation designs
Develop a framework for the effective use of visualisation as scientific evidence
Ability to design and implement interactive visual representations
Good understanding of Statistical Analysis Techniques
Ability to design and execute user studies