Mineralogy and mining are two things that often go hand-in-hand. But scientists at the Carnegie Institution for Science are mining something different – big data, and it may have a significant impact on how minerals are studied and discovered.

There are at least 5200 different known minerals (naturally occurring chemical compounds not formed by biological sources), which have been found and catalogued in hundreds of thousands of different locations around the world. This gives mineralogists millions of data points to work with, but extracting meaning from this data is often difficult.

In a new paper published in American Mineralogist (PDF), a team of scientists have used network theory to gain new insight into the distribution and changes of copper and chromium deposits over time. This approach could lead to the prediction of new minerals or the discovery of new mineral deposits.

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