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v0.1.0 - Initial Release

09 Jan 15:58
@Redliana Redliana
v0.1.0
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Release Notes

v0.1.0 - Initial Release

Release Date: January 8, 2026

We are excited to announce the first public release of CMM Data - the Critical Minerals Modeling Data Access Library developed by Pacific Northwest National Laboratory (PNNL).

Highlights

  • Unified API for accessing 7 different critical minerals datasets
  • 80+ mineral commodities from USGS Mineral Commodity Summaries
  • 3,298 preprocessed documents ready for LLM training
  • Built-in visualizations for production charts and time series
  • Pip-installable with optional dependencies for geo/viz features

New Features

Data Loaders

Loader Dataset Description
USGSCommodityLoader USGS MCS 2023 World production, reserves, U.S. statistics for 80+ commodities
USGSOreDepositsLoader USGS NGDB Geochemistry data with 356 fields, REE analyses
OSTIDocumentsLoader DOE OSTI Technical reports and publications
PreprocessedCorpusLoader CMM Corpus 3,298 documents for NLP/LLM applications
GAChronostratigraphicLoader Geoscience Australia 3D chronostratigraphic model (9 surfaces)
NETLREECoalLoader NETL REE concentrations in coal samples
OECDSupplyChainLoader OECD/IEA Trade data, export restrictions, critical minerals outlook

Convenience Functions

import cmm_data

# View all datasets
cmm_data.get_data_catalog()

# List available commodities
cmm_data.list_commodities()        # 80+ commodities
cmm_data.list_critical_minerals()  # 27 DOE critical minerals

# Quick data loading
cmm_data.load_usgs_commodity("lithi", "world")
cmm_data.load_usgs_commodity("cobal", "salient")

Visualizations

from cmm_data.visualizations.commodity import (
    plot_world_production,
    plot_production_timeseries,
    plot_import_reliance
)

# Create charts
fig = plot_world_production(df, "Lithium", top_n=10)
fig = plot_production_timeseries(df, "Cobalt")
fig = plot_import_reliance(df, "Rare Earths")

Configuration

import cmm_data

# Auto-detects data path from environment or directory structure
config = cmm_data.get_config()

# Manual configuration
cmm_data.configure(
    data_root="/path/to/Globus_Sharing",
    cache_enabled=True,
    cache_ttl_seconds=3600
)

Utilities

  • parse_numeric_value() - Handle USGS special codes (W, NA, --, ranges)
  • parse_range() - Parse range values like ">50", "<100", "100-200"
  • Built-in memory and disk caching with configurable TTL

Critical Minerals Coverage

27 of the 50 DOE Critical Minerals are covered with USGS data:
Aluminum Antimony Arsenic Barite
Beryllium Bismuth Chromium Cobalt
Fluorspar Gallium Germanium Graphite
Indium Lithium Manganese Nickel
Niobium Platinum Group Rare Earths Tantalum
Tellurium Tin Titanium Tungsten
Vanadium Zinc Zirconium/Hafnium

Installation

# Basic installation
pip install cmm-data

# With visualization support
pip install "cmm-data[viz]"

# With geospatial support
pip install "cmm-data[geo]"

# Full installation
pip install "cmm-data[full]"

Requirements

Python: 3.9, 3.10, 3.11, 3.12

Required Dependencies:

  • pandas >= 2.0.0
  • numpy >= 1.24.0

Optional Dependencies:

  • matplotlib >= 3.7.0 (viz)
  • plotly >= 5.15.0 (viz)
  • geopandas >= 0.14.0 (geo)
  • rasterio >= 1.3.0 (geo)
  • fiona >= 1.9.0 (geo)

Documentation

  • README: Comprehensive documentation with examples
  • Sphinx Docs: Full API reference at docs/
  • Examples: Jupyter notebook tutorial and Python scripts
  • CONTRIBUTING: Development setup and guidelines

Package Contents

cmm_data/
├── 62 files total
├── 19 source files (loaders, visualizations, utilities)
├── 17 documentation files (Sphinx + markdown)
├── 5 example files (notebook + scripts)
├── 5 script files (tests, build, demo)
├── 3 GitHub workflow files (CI/CD)
└── Configuration, license, and setup files

Known Limitations

  1. OECD bulk data requires manual download due to Cloudflare protection
  2. NETL geodatabase requires geopandas/fiona installation
  3. GA GeoTIFF files require rasterio for full functionality
  4. Shell commands in documentation assume Unix-like environment

Acknowledgments

This work was supported by the U.S. Department of Energy. Data sources include:

  • U.S. Geological Survey (USGS)
  • Office of Scientific and Technical Information (OSTI)
  • Organisation for Economic Co-operation and Development (OECD)
  • International Energy Agency (IEA)
  • Geoscience Australia
  • National Energy Technology Laboratory (NETL)

What's Next (Planned for v0.2.0)

  • Integration with pymrio for ICIO table analysis
  • Additional visualization types (heatmaps, Sankey diagrams)
  • Data export to Parquet and HDF5 formats
  • Automated data updates from USGS APIs
  • Additional loaders for new data sources

Links

Contributors

  • CMM Team @ Pacific Northwest National Laboratory
  • Claude (AI Assistant) - Code generation and documentation

Full Changelog: https://github.com/PNNL-CMM/cmm-data/commits/v0.1.0

CMM Data v0.1.0 - Critical Minerals Modeling Data Access Library
Pacific Northwest National Laboratory

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