ESG Conflict Risk for Energy Transition Minerals, Global

Global ESG conflict risk assessment for critical energy transition minerals, created by Xiaoyang Lin and last updated in May 2026. The 4.3 MB dataset includes spatial training data, preprocessing and machine learning code, and final risk results categorized by mineral type and region.

Use Cases

• Assessing ESG conflict risks associated with specific critical minerals based on spatial data.
• Replicating the machine learning and feature importance evaluation methodology described in the study.
• Conducting statistical descriptive analysis on mineral risk factors using the provided summary results.
• Spatial analysis of risk distribution by region using the rasterized geospatial data.

Strengths

• Includes comprehensive spatial training datasets and machine learning code for replication.
• Results are categorized by both mineral type and region, as stated in the description.
• Dataset is 4.3 MB, which is a manageable size for download and inspection.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Xiaoyang Lin

Collection Method

Employed ArcGIS for spatial rasterization, R for machine learning, and Excel for statistical analysis.

Freshness

Last updated 2026-05-18 12:05:19; freshness should be verified.

Geography

Global (implied by assessment of minerals by region)