Exploiting mineral data: applications to the diversity, distribution, and social networks of copper minerals

Abstract

We have developed a comprehensive database of copper (Cu) mineral characteristics. These data include crystallographic, paragenetic, chemical, locality, age, structural complexity, and physical property information for the 689 Cu mineral species approved by the International Mineralogical Association (rruff.info/ima). Synthesis of this large, varied dataset allows for in-depth exploration of statistical trends and visualization techniques. With social network analysis (SNA) and cluster analysis of minerals, we create sociograms and chord diagrams. SNA visualizations illustrate the relationships and connectivity between mineral species, which often form cliques associated with rock type and/or geochemistry. Using mineral ecology statistics, we analyze mineral-locality frequency distribution and predict the number of missing mineral species, visualized with accumulation curves. By assembly of 2-dimensional KLEE diagrams of co-existing elements in minerals, we illustrate geochemical trends within a mineral system. To explore mineral age and chemical oxidation state, we create skyline diagrams and compare trends with varying chemistry. These trends illustrate mineral redox changes through geologic time and correlate with significant geologic occurrences, such as the Great Oxidation Event (GOE) or Wilson Cycles.