Using data mining techniques and the collected and harmonised data from Research Aim 1.1, we will discover new patterns from the data themselves.
A scientific analysis within the traditional research model would be to form a hypothesis and then collect the data that will allow it to be proven or disproven. However, the challenge in this situation is that, when given a large amount of harmonised multi-dimensional data, what are the right scientific questions to ask? Complex networks provide a powerful and practical approach to dealing with ‘big-data’ problems by bringing to bear computational tools and theoretical approaches from areas as diverse as graph theory, ecology, statistical mechanics, bioinformatics, numerical analysis, and sociology. The outputs from the analysis will detect patterns and reveal structure in the data otherwise not apparent, and may provide a fundamental change in our understanding of the Antarctic terrestrial environment and its biology.