Our expert: Professor Seokhee Hong, Professor Peter Eades
Our partner: Oracle Research Lab
Funding: Australian Research Council Linkage Grant (2017)
Recent years have seen an explosion in the amount of network data available: software systems, social networks and biological systems have millions of nodes and billions of edges.
The data is complex, as nodes and edges have multivariate attributes.
Exploiting such data sets is hard due to its size and complexity – using current methods, a normal person cannot even deal with a fraction of the data. More efficient ways to understand the data are needed.
We propose to design, implement and evaluate new visualisation methods that scale well with the size of today’s and future (larger) data sets. In common language, a picture is worth a thousand words.
We aim to create such pictures for massive multivariate network data sets
Our project will create new methods for the visual analysis of massive multivariate networks such as complex software systems, social networks, and biological systems.
The results of our project will be used by industry companies in software development, biotechnology, and security, to exploit of their data, by enabling new visualisation methods that allow humans to understand the data.
