CSIRO has a new initiative for dealing with large sets of complex data.

Computational and simulation sciences

Researchers are addressing the problem of data sets that are increasingly large and complex by developing capabilities in the computational and simulation sciences.

• 23 July 2008 | Updated 14 October 2011

• Key science issues
• Focus and outcomes

Key science issues

Research in emerging sciences is increasingly data driven, and traditional data-handling methods may not be able to handle such large datasets. 

Advances in science are increasingly dependent upon the analysis and exploitation of large datasets that are generated by:

• high content, high throughput systems
• large-scale research experiments
• computational science
• systems thinking and integrative science.

Most scientific investigations depend on data acquisition and its analysis, but the acquisition of large amounts of complex data demands new methodology for the analysis of this data.  

Focus and outcomes

CSIRO's research in the computational and simulation sciences is providing the foundation for scientific advances in data-driven sciences.

The purpose of the research is to develop new methodologies to analyse and exploit large and complex datasets. It is part of the international research effort in what is sometimes called 'data-intensive computing'.

Research in computational and simulation sciences deals with datasets that:

• are massive in terms of the volume of data
• may feature temporal complexities (such as streaming data that isn’t synchronised or comes in at different rates)
• cannot be fully understood or used with conventional methods of analysis due to their size and complexity.

CSIRO has more than 20 people working on these science challenges which include:

• rendering 3D images of wood microstructure for the timber industry
• handling unprecedented data volumes from the ASKAP telescope
• detecting anomalous electronic messages for security purposes

Research is being conducted by multidisciplinary teams of researchers with expertise in statistics, mathematics, ICT and other sciences to develop capabilities for working with large datasets.

Read the SOLVE magazine article 'Crunching the information explosion'.