Articles | Volume 18, issue 14
https://doi.org/10.5194/gmd-18-4455-2025
https://doi.org/10.5194/gmd-18-4455-2025
Model description paper
 | 
23 Jul 2025
Model description paper |  | 23 Jul 2025

The OpenMindat v1.0.0 R package: a machine interface to Mindat open data to facilitate data-intensive geoscience discoveries

Xiang Que, Jiyin Zhang, Weilin Chen, Jolyon Ralph, and Xiaogang Ma

Cited articles

4D Initiative: The 4D Initiative: Deep-time Data Driven Discovery, https://4d.carnegiescience.edu/sites/default/files/4D_materials/4D_WhitePaper.pdf, last access: 15 November 2019. 
Bergen, K. J., Johnson, P. A., de Hoop, M. V., and Beroza, G. C.: Machine learning for data-driven discovery in solid Earth geoscience, Science, 363, eaau0323, https://doi.org/10.1126/science.aau0323, 2019. 
Broz, M. E., Cook, R. F., and Whitney, D. L.: Microhardness, toughness, and modulus of Mohs scale minerals, Am. Mineral., 91, 135–142, https://doi.org/10.2138/am.2006.1844, 2006. 
Chamberlain, K. J., Lehnert, K. A., McIntosh, I. M., Morgan, D. J., and Wörner, G.: Time to change the data culture in geochemistry, Nat. Rev. Earth Environ., 2, 737–739, https://doi.org/10.1038/s43017-021-00237-w, 2021. 
Chen, M., Qian, Z., Boers, N., Jakeman, A. J., Kettner, A. J., Brandt, M., Kwan, M. P., Batty, M., Li, W., Zhu, R., and Luo, W.: Iterative integration of deep learning in hybrid Earth surface system modelling, Nat. Rev. Earth Environ., 4, 568–581, https://doi.org/10.1038/s43017-023-00452-7, 2023. 
Download
Short summary
This paper describes an R package as the machine interface to the open data of Mindat.org, one of the world's most widely used databases of mineral species and their distribution. In the past decades, many geoscientists have been using Mindat data, but an open data service has never been fully established. The machine interface described in this paper will be an efficient way to meet the overwhelming data needs.
Share