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<p>This data descriptor presents a globally compiled dataset of major element concentrations for mantle peridotite and pyroxenite xenoliths. The dataset includes whole-rock analyses, constituent mineral compositions, manually collated sample ages, and pressure-temperature estimates predicted using machine learning thermobarometry models. Mantle xenoliths—fragments of lithospheric mantle transported to the surface by kimberlitic and basaltic magmas—serve as direct samples for investigating mantle evolution and heterogeneity. The initial whole-rock and minerals geochemical data were obtained from GEOROC (Geochemistry of Rocks of the Oceans and Continents) database. Following data cleaning and processing, samples were matched by comparing identifiers, references, and coordinates across mineral-specific (clinopyroxene, orthopyroxene, olivine, spinel, and garnet) databases. The results were supplemented by manual verification to ensure accurate grouping of minerals based on their common xenolith origins. This produces a globally consistent mineral assemblage dataset, comprising 19,999 rows of mantle xenolith data from approximately 547 locations. This dataset offers a comprehensive geochemical foundation for mantle-related studies.</p>

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A global mantle xenolith bulk-rock and paired-mineral dataset

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月18日

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  • Ben Qin,
  • Tao Sun,
  • Litong Li,
  • Dongya Zou

摘要

This data descriptor presents a globally compiled dataset of major element concentrations for mantle peridotite and pyroxenite xenoliths. The dataset includes whole-rock analyses, constituent mineral compositions, manually collated sample ages, and pressure-temperature estimates predicted using machine learning thermobarometry models. Mantle xenoliths—fragments of lithospheric mantle transported to the surface by kimberlitic and basaltic magmas—serve as direct samples for investigating mantle evolution and heterogeneity. The initial whole-rock and minerals geochemical data were obtained from GEOROC (Geochemistry of Rocks of the Oceans and Continents) database. Following data cleaning and processing, samples were matched by comparing identifiers, references, and coordinates across mineral-specific (clinopyroxene, orthopyroxene, olivine, spinel, and garnet) databases. The results were supplemented by manual verification to ensure accurate grouping of minerals based on their common xenolith origins. This produces a globally consistent mineral assemblage dataset, comprising 19,999 rows of mantle xenolith data from approximately 547 locations. This dataset offers a comprehensive geochemical foundation for mantle-related studies.