This web service delivers data from an aggregation of sources, including several Geoscience Australia databases (provinces (PROVS), mineral resources (OZMIN), energy systems (AERA, ENERGY_SYSTEMS) and water (HYDROGEOLOGY). Information is grouped based on a modified version of the Australian Bureau of Statistics (ABS) 2021 Indigenous Regions (IREG). Data covers population centres, top industries, a regional summary, groundwater resources and uses, energy production and potential across six sources and two energy storage options. Mineral production and potential covers 36 commodities that are grouped into 13 groups.

This web service delivers data from an aggregation of sources, including several Geoscience Australia databases (provinces (PROVS), mineral resources (OZMIN), energy systems (AERA, ENERGY_SYSTEMS) and water (HYDROGEOLOGY). Information is grouped based on a modified version of the Australian Bureau of Statistics (ABS) 2021 Indigenous Regions (IREG). Data covers population centres, top industries, a regional summary, groundwater resources and uses, energy production and potential across six sources and two energy storage options. Mineral production and potential covers 36 commodities that are grouped into 13 groups.

<div>These videos provide tutorials on how to use the Geoscience Australia Data portal in the classroom. They include a guide for basic navigation, how to load 2D map data sets (elevation, surface geology and critical minerals) as well as accessing a 3D data model (earthquakes).&nbsp;Additionally, they demonstrate how to directly compare multiple data and how to share collated data through a shareable link.</div><div>Videos included:</div><div>-&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Introduction to using the Geoscience Australia Data Portal (2:15)</div><div>-&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;How to access elevation, surface geology and critical minerals data in the Geoscience Australia Data Portal (4:26)</div><div>- How to view the global distribution of earthquakes using the Geoscience Australia Data Portal (2:51)</div><div><br></div><div>These videos are suitable for use by secondary students and adults.</div>

<div>This guide and template details data requirements for submission of mineral deposit geochemical data to the Critical Minerals in Ores (CMiO) database, hosted by Geoscience Australia, in partnership with the United States Geological Survey and the Geological Survey of Canada. The CMiO database is designed to capture multielement geochemical data from a wide variety of critical mineral-bearing deposits around the world. Samples included within this database must be well-characterized and come from localities that have been sufficiently studied to have a reasonable constraint on their deposit type and environment of formation. As such, only samples analysed by modern geochemical methods, and with certain minimum metadata attribution, can be accepted. Data that is submitted to the CMiO database will also be published via the Geoscience Australia Portal (portal.ga.gov.au) and Critical Minerals Mapping Initiative Portal (https://portal.ga.gov.au/persona/cmmi).&nbsp;</div><div><br></div>

<div>Geological maps are powerful models for visualizing the complex distribution of rock types through space and time. However, the descriptive information that forms the basis for a preferred map interpretation is typically stored in geological map databases as unstructured text data that are difficult to use in practice. Herein we apply natural language processing (NLP) to geoscientific text data from Canada, the U.S., and Australia to address that knowledge gap. First, rock descriptions, geological ages, lithostratigraphic and lithodemic information, and other long-form text data are translated to numerical vectors, i.e., a word embedding, using a geoscience language model. Network analysis of word associations, nearest neighbors, and principal component analysis are then used to extract meaningful semantic relationships between rock types. We further demonstrate using simple Naive Bayes classifiers and the area under receiver operating characteristics plots (AUC) how word vectors can be used to: (1) predict the locations of “pegmatitic” (AUC = 0.962) and “alkalic” (AUC = 0.938) rocks; (2) predict mineral potential for Mississippi-Valley-type (AUC = 0.868) and clastic-dominated (AUC = 0.809) Zn-Pb deposits; and (3) search geoscientific text data for analogues of the giant Mount Isa clastic-dominated Zn-Pb deposit using the cosine similarities between word vectors. This form of semantic search is a promising NLP approach for assessing mineral potential with limited training data. Overall, the results highlight how geoscience language models and NLP can be used to extract new knowledge from unstructured text data and reduce the mineral exploration search space for critical raw materials.</div><div><br></div><div><strong>Citation: </strong>Lawley, C. J. M., Gadd, M. G., Parsa, M., Lederer, G. W., Graham, G. E., and Ford, A., 2023, Applications of Natural Language Processing to Geoscience Text Data and Prospectivity Modeling: Natural Resources Research. https://doi.org/10.1007/s11053-023-10216-1</div>

<div>Disruptions to the global supply chains of critical raw materials (CRM) have the potential to delay or increase the cost of the renewable energy transition. However, for some CRM, the primary drivers of these supply chain disruptions are likely to be issues related to environmental, social, and governance (ESG) rather than geological scarcity. Herein we combine public geospatial data as mappable proxies for key ESG indicators (e.g., conservation, biodiversity, freshwater, energy, waste, land use, human development, health and safety, and governance) and a global dataset of news events to train and validate three models for predicting “conflict” events (e.g., disputes, protests, violence) that can negatively impact CRM supply chains: (1) a knowledge-driven fuzzy logic model that yields an area under the curve (AUC) for the receiver operating characteristics plot of 0.72 for the entire model; (2) a naïve Bayes model that yields an AUC of 0.81 for the test set; and (3) a deep learning model comprising stacked autoencoders and a feed-forward artificial neural network that yields an AUC of 0.91 for the test set. The high AUC of the deep learning model demonstrates that public geospatial data can accurately predict natural resources conflicts, but we show that machine learning results are biased by proxies for population density and likely underestimate the potential for conflict in remote areas. Knowledge-driven methods are the least impacted by population bias and are used to calculate an ESG rating that is then applied to a global dataset of lithium occurrences as a case study. We demonstrate that giant lithium brine deposits (i.e., >10&nbsp;Mt Li2O) are restricted to regions with higher spatially situated risks relative to a subset of smaller pegmatite-hosted deposits that yield higher ESG ratings (i.e., lower risk). Our results reveal trade-offs between the sources of lithium, resource size, and spatially situated risks. We suggest that this type of geospatial ESG rating is broadly applicable to other CRM and that mapping spatially situated risks prior to mineral exploration has the potential to improve ESG outcomes and government policies that strengthen supply chains. <b>Citation:</b> Haynes M, Chudasama B, Goodenough K, Eerola T, Golev A, Zhang SE, Park J and Lèbre E (2024) Geospatial Data and Deep Learning Expose ESG Risks to Critical Raw Materials Supply: The Case of Lithium. <i>Earth Sci. Syst. Soc. </i>4:10109. doi: 10.3389/esss.2024.10109

<div>High purity quartz (HPQ) is the only naturally occurring and economically viable source for the production of silicon. Silicon is a critical mineral, and a key component in modern technologies such as semiconductors and photovoltaic cells. Critical minerals support the move towards a greater reliance on electrification, renewable energy sources and economic security. The global transition to net zero carbon emissions means there is a growing need for new discoveries of HPQ to supply the silicon production chain. High purity quartz deposits are identified in a multitude of geological settings, including pegmatites, hydrothermal veins, sedimentary accumulations and quartzite; however, deposits of sufficient volume and quality are rare. Quartz is abundant throughout Australia, but the exploration and discovery of HPQ occurrences is notably under-reported, making assessment of the HPQ potential in Australia extremely difficult. This paper presents a much-needed summary of the state of the HPQ industry, exploration and deposit styles in Australia. <b>Citation:</b> Jennings, A., Senior, A., Guerin, K., Main, P., & Walsh, J. (2024). A review of high-purity quartz for silicon production in Australia. <i>Australian Journal of Earth Sciences</i>, 1–13. https://doi.org/10.1080/08120099.2024.2362296

High-purity quartz (HPQ) is the only naturally occurring and economically viable source for the production of silicon. Silicon is a critical mineral, and a key component in modern technologies such as semiconductors and photovoltaic cells. Critical minerals support the move towards a greater reliance on electrification, renewable energy sources and economic security. The global transition to net zero carbon emissions means there is a growing need for new discoveries of HPQ to supply the silicon production chain. HPQ deposits are identified in a multitude of geological settings, including pegmatites, hydrothermal veins, sedimentary accumulations and quartzite; however, deposits of sufficient volume and quality are rare. Quartz is abundant throughout Australia, but the exploration and discovery of HPQ occurrences are notably under-reported, making assessment of the HPQ potential in Australia extremely difficult. This paper presents a much-needed summary of the state of the HPQ industry, exploration and deposit styles in Australia. KEY POINTS: 1. High-purity quartz (HPQ) is a key material for the manufacture of photovoltaic cells, semiconductors and other high-technology applications. 2. HPQ can be recovered from a variety of different source rocks in a range of geological settings. 3. Currently, the HPQ industry in Australia is under-utilised for high-technology applications, and historical exploration and mining records are under-reported and opaque. 4. This review presents an outline of the characteristics, processing requirements and end uses of HPQ, and a summary of the operations, deposits, exploration targets and known occurrences of HPQ in Australia. <b>Citation:</b> Jennings, A., Senior, A., Guerin, K., Main, P., & Walsh, J. (2024). A review of high-purity quartz for silicon production in Australia. <i>Australian Journal of Earth Sciences</i>, 1–13. https://doi.org/10.1080/08120099.2024.2362296

<div>Critical minerals are the minerals and elements essential for modern technologies, economies and national security. However, the supply chains of these minerals may be vulnerable to disruption thereby making the study of these minerals, from source to product, of primary importance. </div><div><br></div><div>The global transition to net-zero emissions is driving accelerated consumption of critical minerals, particularly driven by the increase in demand for technologies such as solar photovoltaics (PV) and semiconductors (Department of Industry, Science and Resources [DISR], 2022; 2023). In parallel, the phasing out of, for example, traditional machinery and manufacturing processes reliant on hydrocarbon resources (Ali et al., 2017; Bruce et al., 2021; International Energy Agency [IEA], 2021; 2023; Skirrow et al., 2013) is further adding to the global demand. High Purity Quartz (HPQ) forms just one of these critical minerals, and is the primary raw material for the production of High Purity Silica (HPS) and Silicon (Si) for use in products ranging from solar PVs to semiconductors. </div><div><br></div><div>The current list of minerals classified as critical is now up to 31 (Department of Industry, Science and Resources [DISR], 2022; 2023). This diversity of critical minerals is also promoting a new focus on the exploration for i) new styles of mineralisation that might host sufficient volumes of critical minerals, and ii) a re-examination of existing minerals systems knowledge in order to help mineral explorers make new discoveries to help support the increasing demand. </div><div><br></div><div>At present, the main global suppliers of HPQ are the United States, Canada, Norway, Brazil, Russia and India (Pan et al., 2022). In Australia, there has been a paucity of exploration and development of HPQ mineral deposits and, despite the potential that Australia holds for the exploration and discovery of potentially significant HPQ occurrences, Simcoa Operations Pty Ltd. (Figure 1) represents the only operator currently mining HPQ, and the only manufacturer of high purity silicon in Australia (Simcoa, 2020). </div><div><br></div><div>Australia is well-positioned to incentivise the exploration, discovery and supply of raw materials, and significantly expand onshore silicon production capacity (PricewaterhouseCoopers, 2022). Research presented here highlights the opportunity that Australia has in making a positive contribution to meeting the global demand for HPQ required for high-technology applications and the transition to a net zero economy.&nbsp;</div><div><br></div>Abstract presented at the 2024 Annual Geoscience Exploration Seminar (AGES)

<div>This record one in a series of reports detailing the geochemical and mineralogical results of sampling collected at mine waste sites across Australia as part of Geoscience Australia's Exploring for the Future program. It presents new data and information regarding the tenor rare earth elements, ore commodities (lead, zinc and silver) and other trace metals, at the Cannington silver and lead mine located in Queensland’s Northwest Minerals Province.</div><div><br></div><div>Geoscience Australia’s Exploring for the Future program provides precompetitive information to inform decision-making by government, community and industry on the sustainable development of Australia's mineral, energy and groundwater resources. By gathering, analysing and interpreting new and existing precompetitive geoscience data and knowledge, we are building a national picture of Australia’s geology and resource potential. This leads to a strong economy, resilient society and sustainable environment for the benefit of all Australians. This includes supporting Australia’s transition to net zero emissions, strong, sustainable resources and agriculture sectors, and economic opportunities and social benefits for Australia’s regional and remote communities. The Exploring for the Future program, which commenced in 2016, is an eight year, $225m investment by the Australian Government.</div><div><br></div>