SiroSOM self organising maps: complex datasets made simple

The challenge

Extracting knowledge from complex datasets

As technology and engineering evolve, the ability to measure variables increases and the volume of data generated can be overwhelming. Extracting useful knowledge from geological and other data is crucial to the mining industry in targeting areas for exploration and planning processing strategies for ores and minerals. Often this information is not conveniently available in one master data package but is contained in a number of different datasets or data forms.

For example, data may be:

• descriptive, such as a soil or rock texture
• subjective, such as a person's judgement on a bacterial bloom's density
• a continual measurement such as a seismic wave form
• point data such as drill-hole data.

Synthesising this volume of information from different sources into a usable form can be time-consuming and technically challenging.

Our response

Data analysis tool to create accurate geological maps

We developed SiroSOM, a data analysis tool that uses the self-organising map (SOM) technique that works by grouping data which exhibit common characteristics. The method allows industry and research to integrate data such as:

• geophysical
• geochemical
• visual attributes.

SiroSOM has the ability to consider all data irrespective of data type. Similarly, SiroSOM can also manage data that may be spatially related airborne geophysics and geochemistry. This approach improves routine preparation of geological maps to allow industry to quickly identify promising prospecting targets as well as highlight potential hazards to exploration, mining and processing.

The results

Time-saving data-crunching

We have sold more than 40 licenses of SiroSOM since it was first developed.

Although initially developed for and popular in mining and exploration, SiroSOM is increasingly sought after in social sciences, business and forestry sectors.