High-dimensional data is, by its nature, difficult to visualise. Many current techniques involve reducing the dimensionality of the data, which results in a loss of information. ...
Never before in history data has been generated at such high volumes as it is today. Exploring and analyzing the vast volumes of data becomes increasingly difficult. Information vi...
Our ability to generate ever-larger, increasingly-complex data, has established the need for scalable methods that identify, and provide insight into, important variable trends and...
Luke J. Gosink, John C. Anderson, E. Wes Bethel,...
Due to complexity, modern visualization techniques for large data volumes and complex interrelationships are difficult to understand for non-expert users and even for expert user...
—Graph visualization has been widely used to understand and present both global structural and local adjacency information in relational datasets (e.g., transportation networks, ...