NEW FRONTIERS IN MINERALOGY: DATA-DRIVEN EXPLORATION OF COMPLEX, EVOLVING EARTH AND PLANETARY SYSTEMS

Compelling questions in Earth, planetary, and life science demand breaching the silos of scientific fields and harnessing the integrated power of their diverse data resources. An unprecedented opportunity lies in combining vast mineral data resources and applying data science and advanced visualization techniques to address multidisciplinary questions untouchable by on field alone.

Mineral informatics and data-driven discovery in Earth and planetary science is facilitating rapid advancement of our understanding of the mineralogy of our planet and neighboring bodies, how they have evolved through deep time and what geologic processes characterize each stage of planetary evolution, and how, on Earth, life is dynamically intertwined with the geosphere. Data-driven investigations utilizing innovative methods (e.g., mineral network analysis, mineral association analysis) to characterize the multidimensional relationships amongst the myriad attributes of these systems. Mineral informatics methods have led to the discovery of new mineral localities,¹ the prediction of mineral inventories at Mars analog sites,¹ mineralogical biosignatures from the planetary scale to the sample scale,² complex mineral compositions on Mars via X-ray diffraction data alone,³ and quantification of the role of water, life, and rare elements in Earth’s mineralogical makeup.⁴

Through integrated, multidisciplinary exploration, we are poised to embark on a transformative journey, crossing new frontiers in mineralogy and advancing our understanding of complex, evolving Earth and planetary systems. This synergistic approach promises groundbreaking discoveries, uncovering the fundamental interconnections that underpin our planet's complexly intertwined geologic and biologic history.

[1] Morrison et al (2023) Machine learning approaches for predictive mineralogy in Earth and planetary science: A study in mineral association analysis, PNAS Nexus, 2(5)

[2] Morrison et al (2020) Exploring carbon mineral systems: Recent advances in C mineral evolution, mineral ecology, and network analysis, Frontiers, 8, 208

[3] Morrison et al (2018) Predicting Multi-Component Mineral Compositions in Gale crater, Mars with Label Distribution Learning, AGU, P21I-3438

[4] Hazen & Morrison (2022) On the paragenetic modes of minerals: A mineral evolution perspective, Am Min, 107, 1262–1287