Geoscientific data, derived from activities such as field sampling, core or chip logging and face mapping, is the foundation for geological and financial evaluation of ore bodies, mine design and the daily decision-making on an operational mine.

Thus it is critical that the capture and management of such data, a task often assigned to inexperienced geologists, is done with due attention to maintaining its integrity and providing quality assurance.

This is best done by

What is data?

Groups of information that represent the qualitative or quantitative attributes of something

If you take something and you measure it, analyse it or describe it, you will derive some form of data about it

What data does a geologist deal with?

A scientist’s data forms the body of evidence with which we test our hypotheses and draw conclusions. In geology this can take many forms. Some example include:

• Positioning: Where we collect samples, perform mapping, drill a hole, take a photograph
• Analytical: Laboratory or other analytical results for a sample (grade, XRF, densities, etc)
• Geological observations: Our primary description of the lithology, mineralogy, alteration, structures and so forth
• Geological interpretations: Our secondary descriptions, based on an understanding of the relative position of lithologies and other factors
• Audit and management information: When? Who? Why?
• Images: Photographs, scans  

The role of geoscientific data

In our own world of geology, we sometimes forget the importance of the data we collect to the world beyond our own direct needs. Eventually, that data, or an interpretation thereof, is used for everything from scientific publications through to resource evaluations, mine design through to stock exchange listings. It is the bedrock for all major decisions that will get taken, be they

• Whether to proceed with another phase of exploration
• Whether to mine or sell the asset
• How to design a mine to make the most of the ore body
• What sort of safety mechanisms must be put in place
• Do I invest in this company or not?

Why is data integrity so important?

The many potential uses of the data place a huge responsibility on us to ensure that all the relevant data is collected when possible, and is stored in a way that is both true to our understanding and in a format that is useable for these myriad of applications.

By the time someone else gets around to using the data we collect, they usually assume that it is correct, representative and unbiased. This is just the way we are – we cannot deal with the complexity of interrogating the underlying data when we are thinking at a different level, or abstraction. However, as soon as an error is detected, the confidence in the entire data set starts to fall, to the point when even accurate data becomes tainted.

The underlying principle of SAMREC and other resource classification systems is the level of confidence in the interpretations and estimates made, based on specific geoscientific evidence and knowledge. If your data has integrity issues, then you should not be using it in your interpretations, which could lead to lower resource classifications.  

Every project these days undergoes internal and external audits to ensure that we are following consistent, proper procedures in the way we collect and handle our data. This means that you will be required to show that you are doing things the right way, and not measuring things one way one day and differently the next, and not doing silly (illegal) things like editing your assay result files when you get them back from the labs.  

Finally, you are spending tens of millions, if not more, on your drilling, logging, sampling, analyses, and so forth. Once you are finished with all of this, all you have to show for your efforts is the data. So look after it, or you’re throwing money down the toilet.  

Common Problems with Data Collection

Logging standard

One of the most common problems is inconsistency in what and how geological features are described. We all come from different backgrounds, have had different educations, speak a variety of languages, and then we get put on a project together and are expected to see and describe the same things when we look at a rock. But if we describe our data differently from one another, or inconsistently ourselves over time, we cannot treat it as a homogenous data set and it loses its value.

To get around this, you need to define

• What data should be collected
• What the different parameters are
• What terms may be used for each parameter – and ensure that everyone means the same thing when they talk about X (conglomerate vs. gravel vs. …)
• What conventions apply (coordinates, dips, bearings, etc)
• Should be agreed to by all geologists
• All new geologists should be trained in the new logging standard
• A document should be produced that all geologists can read and use as their reference
• Any system used to record the data should be configured to allow you to represent the data in a way that is both simple and true to the meaning of the data.
• You should NOT be having to try to fit your data into a capture tool that forces you to compromise, otherwise you may be harming the integrity of your observations.