Data-Driven Discovery in Mineralogy: Recent Advances in Data Resources, Analysis, and Visualization

摘要

Large and growing data resources on the diversity,distribution,and properties of minerals are ushering in a new era of data-driven discovery in mineralogy.The most comprehensive international mineral data-base is the IMA database,which includes information on more than 5400 approved mineral species and their properties,and the mindat.org data source,which contains more than 1 million species/locality data on minerals found at more than 300 000 localities.Analysis and visualization of these data with diverse techniques-including chord diagrams,cluster diagrams,Klee diagrams,skyline diagrams,and varied methods of network analysis-are leading to a greater understanding of the co-evolving geosphere and biosphere.New data-driven approaches include mineral evolution,mineral ecology,and mineral network analysis-methods that collectively consider the distribution and diversity of minerals through space and time.These strategies are fostering a deeper understanding of mineral co-occurrences and,for the first time,facilitating predictions of mineral species that occur on Earth but have yet to be discovered and described.