A Global Mining Dataset

Summary

The International Council on Mining and Metals (ICMM) is a mining industry group that was founded in London in 2001. In September, they released a Global Mining Dataset containing over 8,000 mines and other related assets around the globe. Below is a heatmap of the assets they catalogued in this dataset. In this post, I'll explore ICMM's mining dataset. My Workstation I'm using a 5.7 GHz AMD Ryzen 9 9950X CPU. It has 16 cores and 32 threads and 1.2 MB of L1, 16 MB of L2 and 64 MB of L3 cache. It has a liquid cooler attached and is housed in a spacious, full-sized Cooler Master HAF 700 computer case. The system has 96 GB of DDR5 RAM clocked at 4,800 MT/s and a 5th-generation, Crucial T700 4 TB NVMe M.2 SSD which can read at speeds up to 12,400 MB/s. There is a heatsink on the SSD to help keep its temperature down. This is my system's C drive. The system is powered by a 1,200-watt, fully modular Corsair Power Supply and is sat on an ASRock X870E Nova 90 Motherboard. I'm running Ubuntu 24 LTS via Microsoft's Ubuntu for Windows on Windows 11 Pro. In case you're wondering why I don't run a Linux-based desktop as my primary work environment, I'm still using an Nvidia GTX 1080 GPU which has better driver support on Windows and ArcGIS Pro only supports Windows natively. Installing Prerequisites I'll use Python 3.12.3 and a few other tools to help analyse the data in this post. $ sudo add-apt-repository ppa:ubuntugis/ubuntugis-unstable $ sudo apt update $ sudo apt install \ jq \ python3-pip \ python3.12-venv I'll set up a Python Virtual Environment and install an OSM vector tile data extraction utility I wrote last year. $ python3 -m venv ~/.osm $ source ~/.osm/bin/activate $ git clone https://github.com/marklit/tiles2columns \ ~/tiles2columns $ python -m pip install \ -r ~/tiles2columns/requirements.txt I'll use DuckDB v1.3.0, along with its H3, JSON, Lindel, Parquet and Spatial extensions, in this post. Normally I try and use the latest release of DuckDB but v1.4.0 has an ...