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11 Oct 2010 - Technology – GIM Suite

Improving the quality of geoscientific information

“Garbage In – Garbage Out”. Almost everyone has heard this phrase and most would agree with its core message, but in essence, it’s a cop out! Why? Because it is used to deflect criticism from systems that return useless or poor quality information and answers.

Today, more than any other time in history, data are business assets. All businesses that collect, store, manage, interrogate, abstract, use and deliver data, especially digital data, need to be mindful of its origins, context, relevance and usage. As a consequence businesses are increasingly turning their attention to data quality issues in order to exploit the value of their data & information assets.

There are numerous data assets in the mining industry. Those to be considered here are the original observations and measurements that represent an understanding of the subsurface (i.e. the geoscientific information). These subsurface data types are used as inputs for modelling (both economic and operational) and are interpreted to provide information upon which decisions will be made.

Therefore the value of the original observations and measurements to a mining business extends well beyond the cost of drilling or sample analyses etc. When compared to other asset classes, geoscientific data have properties that are very different from more tangible assets such as truck fleets, dragline buckets or explosive inventories for example. If we accept that data are business assets, then we should also accept that they should be managed as aggressively as any other asset class.

Yacopetti, M and Mundell, S, 2010. Improving the quality of geoscientific information, in Bowen Basin Symposium 2010 – Back in (the) Black, Geological Society of Australia Inc. Coal Geology Group and the Bowen Basin Geologists Group, Mackay, October 2010, pp 97 -100.

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