Information visualisation is the use of enhanced Graphical User Interfaces (GUIs) to communicate and interact with complex data sets such as social networks, multiattribute tables, and financial data.
Pages of text and numbers are not the most effective way to communicate or understand information. People prefer pictures. Interactive GUIs, where relevant attributes are mapped to qualities such as position, size, shape and colour, make it much easier to dynamically explore, manipulate and query data using both standard mouse and touch interactions.
The issues faced by biologists, for example, have driven many of the advances in information visualisation that we’ve made in the Institute. The sheer volume of data generated - in everything from molecular biology to environmental sciences - presents many challenges.
We’ve devised novel visualisation techniques that allow biologists not only to see what’s going on in their data, but also communicate their discoveries to others.
We’ve applied our expertise and research to a wide range of issues in the life sciences arena. These include the integration of disparate biological data sources in ecology; and identifying errors in data sets that include pedigrees, classifications and genomes.
Kennedy, J. (2010). A Survey of Multiple Tree Visualisation. Information Visualization, 9, (4), 235-252.
Law, A. (2011). Visualising Errors in Animal Pedigree Genotype Data. Computer Graphics Forum , 30, (3), 1011-1020.
Buono, P. (2011). Research directions in data wrangling: Visualizations and transformations for usable and credible data. Information Visualization, October 2011, (10), 271-288.
Kennedy, J. (2008). Multiform Views of Multiple Trees. In: (Ed.) Proceedings of IV2008, , () ( ed.). (pp. 252-257). London, UK: . IEEE Computer Society Press.
Law, A. (2012). VIPER: a visualisation tool for exploring inheritance inconsistencies in genotyped pedigrees. BMC Bioinformatics, 13 (Suppl 8), (S5), .
Kennedy, J. (2008). Concept Relationship Editor: A visual interface to support the assertion of synonymy relationships between taxonomic classifications. In: Börner, K.,
Roberts, J. (Eds.) Visualization and Data Analysis 2008, Proceedings of the SPIE, 6809, () ( ed.). (pp. 680906-680912). San Jose, CA: . Society of Photo-Optical Instrumentation Engineers, Bellingham, WA, ETATS-UNIS .