Global Copper Deposit Dataset: A New Open-Source Database for Advanced Data Analysis and Exploration Targeting

Abstract

Global copper supply faces systemic challenges, mainly from geographically concentrated reserves, aging mines and declining ore grades. One way to help overcome these issues is with technology. In this study, we present a new, open-source global copper deposit dataset (GCDD), facilitating artificial intelligence-driven data analysis for exploration targeting and improving our understanding of copper mineralizing systems and their mappable expressions. The newly developed GCDD hosts information about 1483 copper deposits worldwide, capturing key deposit attributes such as location, genetic type, metallogenic age, mineral assemblage, grade and tonnage. Rigorous manual validation procedures ensured data accuracy and consistency. The GCDD, intended as a standardised, comprehensive resource for copper deposit exploration and geoscientific research, was established by systematically integrating copper deposits information from three authoritative open-source databases: Mindat, MRDS, and the Mineral Evolution Database. The data extracted from these sources were supplemented with information sourced from peer-reviewed literature. Whilst Mindat, MRDS and the Mineral Evolution Database each contain important copper deposit data, they lack standardised genetic classifications and quantitative mineralogical records and, therefore, do not lend themselves well to exploration targeting or advanced modelling. The GCDD, on the other hand, supports both (i) traditional metallogenic studies and resource assessments, and (ii) advanced analyses such as network-based mapping of mineral co-occurrence patterns and association rule mining to uncover intrinsic links between mineral assemblages and copper deposit types. As such, it can facilitate critical mineral assessment, spatiotemporal metallogenic analysis, and data-driven exploration targeting of sustainable future copper supply.