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The open data movement has brought revolutionary changes to the field of mineralogy. With a growing number of datasets made available through community efforts, researchers are now able to explore new scientific topics such as mineral ecology, mineral evolution and new classification systems. The recent results have shown that the necessary open data coupled with data science skills and expertise in mineralogy will lead to impressive new scientific discoveries. Yet, feedback from researchers also reflects the needs for better FAIRness of open data, that is, findable, accessible, interoperable and reusable for both humans and machines. In this paper, we present our recent work on building the open data service of Mindat, one of the largest mineral databases in the world. In the past years, Mindat has supported numerous scientific studies but a machine interface for data access has never been established. Through the OpenMindat project we have achieved solid progress on two activities: (1) cleanse data and improve data quality, and (2) build a data sharing platform and establish a machine interface for data query and access. We hope OpenMindat will help address the increasing data needs from researchers in mineralogy for an internationally recognized authoritative database that is fully compliant with the FAIR guiding principles and helps accelerate scientific discoveries. [ABSTRACT FROM AUTHOR]

Integrating mineralogy with data science is critical to modernizing Earth materials research and its applications to geosciences. Data were compiled on 95 650 garnet sample analyses from a variety of sources, ranging from large repositories (EarthChem, RRUFF, MetPetDB) to individual peer-reviewed literature. An important feature is the inclusion of mineralogical "dark data" from papers published prior to 1990. Garnets are commonly used as indicators of formation environments, which directly correlate with their geochemical properties; thus, they are an ideal subject for the creation of an extensive data resource that incorporates composition, locality information, paragenetic mode, age, temperature, pressure, and geochemistry. For the data extracted from existing databases and literature, we increased the resolution of several key aspects, including petrogenetic and paragenetic attributes, which we extended from generic material type (e.g., igneous, metamorphic) to more specific rock-type names (e.g., diorite, eclogite, skarn) and locality information, increasing specificity by examining the continent, country, area, geological context, longitude, and latitude. Likewise, we utilized end-member and quality index calculations to help assess the garnet sample analysis quality. This comprehensive dataset of garnet information is an open-access resource available in the Evolutionary System of Mineralogy Database (ESMD) for future mineralogical studies, paving the way for characterizing correlations between chemical composition and paragenesis through natural kind clustering (Chiama et al., 2022; 10.48484/camh-xy98). We encourage scientists to contribute their own unpublished and unarchived analyses to the growing data repositories of mineralogical information that are increasingly valuable for advancing scientific discovery. [ABSTRACT FROM AUTHOR]

Abstract: Multiple Critical Zone Observatories (CZO) have been established in recent years in the USA and other international settings to conduct collaborative research on processes that occur at and near Earth’s surface, also known as the Critical Zone (CZ). Data documentation and data sharing are two persistent problems facing the CZOs that impede the ability for cross-site comparisons and integrated analysis. In this study, a relational database was developed for CZ rock and regolith geochemical data – CZChemDB. There are a total of 24 interrelated tables in the database, each representing different aspects of CZ features. The main data group includes tables of locations, sites, samples, subsamples, preparation/treatments, laboratory-analysis and data values. The meta-data group includes tables of methods, references, and data quality. Lookup tables (variables, units, etc.) contain lists of “controlled” vocabularies. The CZChemDB is currently implemented in the MS Access database management system. It is expected to be integrated into the EarthChem portal by summer of 2011 for broader online accessibility and usability. This integration also complements the EarthChem’s global geochemistry database with CZ regolith data. The structure of the CZChemDB is simple, straightforward, and flexible so that it has potential to accommodate other chemical data collected from CZOs, such as pore fluid data. Furthermore, the development of CZChemDB represents the first attempt toward the standardization of geochemical data documentation and data sharing among CZOs. This effort will establish a model to bridge the connections between data acquisition, data management, data sharing, and data searching/discovering that are all essential but weak in terms of linkages within most geoscience research projects. [Copyright &y& Elsevier]