Cet ensemble de données fournit de l’information sur le secteur de l’activité minière en Ontario, en incluant une compagnie, un projet, et un type d’activités. Pour plus d’information, référez-vous à Géologie Ontario, un entrepôt en ligne qui contient toutes les données digitales publiquement disponibles qui sont trouvées sur les sites Internet suivants : http://www.geologyontario.mndm.gov.on.ca/ or http://www.mndm.gov.on.ca/fr/mines-et-des-mineraux/applications/ogsearth/rapports-dactivite-sur-lexploration-des-mineraux

This model is derived from geological, geophysical and other forms of geodata. Feature extraction used deep learning. Predictive modelling made use of the deep ensemble method. Displayed is a Pan-Canadian probability map of mineral potential of graphite. This map was generated using known graphite deposits and occurrences and their associated features. Higher probability values highlight areas with an increased probability of graphite mineral systems.

Un claim minier (connue par le ministère du Développement du Nord et des Mines (MNDM) comme un claim minier non breveté) est une zone de terres de la Couronne qui est jalonnée par un individu ou une entreprise d'exploration minière qui détient une licence de prospection valide. Cela confère à l'individu ou à la société d'exploration minière , des intérêts miniers légaux sur les terrains jalonnés comme le prévoit la Loi sur les mines de l'Ontario. «Claim» désigne une parcelle de terre, y compris des terres sous l'eau, qui a été jalonnée et enregistrée conformément à la Loi sur les mines et aux règlements. En ce qui concerne le statut «en attente» sur un claim minier non breveté signifient qu'il n'est pas officiellement actif et qu'il est indiqué sur les cartes pour indiquer qu'il y a une activité sur les terres de la Couronne en attente d'approbation. Les délais du statut «en attente» peuvent être des jours, des semaines, des mois ou même des années. Chaque cas est unique. Les codes de statut pour les claims miniers non brevetés sont actifs, annulés et en attente.

This model is derived from geological and geophysical data, which is processed using deep learning and natural language processing techniques. Displayed is a Pan-Canadian probability map indicating the likelihood of discovering next-generation lithium-cesium-tantalum (LCT) pegmatites. This map was generated using known Canadian LCT pegmatites and their associated geospatial features, incorporating geological and geophysical data analyzed through deep learning and natural language processing techniques. Higher probability values highlight areas with an increased likelihood of hosting next-generation deposits, making this map a valuable tool for decision-making.

This theme includes data from all metal monitoring stations in the waters of rivers in Quebec and the St. Lawrence River since 2008. It includes the stations of the “Special Metals” tour, the stations of Réseau-Fleuve and Réseau-Rivières as well as the stations of the “Grand Nord” project.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

This dataset provides information related to the top-spending off-mine-site exploration and deposit appraisal projects in Canada for the given reference year. The dataset is maintained by the Lands and Minerals Sector, Natural Resources Canada, and forms the basis for the annual Map of Top 100 Exploration and Deposit Appraisal Projects in Canada. Related product: - **[Principal Mineral Areas, Producing Mines, and Oil and Gas Fields (900A)](https://open.canada.ca/data/en/dataset/000183ed-8864-42f0-ae43-c4313a860720)**

This dataset contains primary processing facilities (e.g., smelters and refineries), mines and advanced projects related to Canada’s 34 critical minerals. Advanced projects are those with mineral reserves or resources (measured or indicated), the potential viability of which is supported by a preliminary economic assessment or a prefeasibility/feasibility study. These sites process, produce or consider producing at least one of Canada's critical minerals, but other minerals and metals may also be present. This dataset contains links that direct to non-Government of Canada websites that are not subject to the Privacy Act, the Official Languages Act or the Standard on Web Accessibility. Please see our terms and conditions for more information (https://www.nrcan.gc.ca/terms-and-conditions/10847). Primary processing facilities and mines data are sourced from Map 900A, Principal mineral areas, producing mines, and oil and gas fields in Canada. Data on advanced critical minerals projects are produced and published annually by Natural Resources Canada, in collaboration with provinces and territories. Data are compiled from a variety of public sources. Natural Resources Canada does not assume responsibility for errors or omissions. Please report any recommended revisions.

Prospectivity model highlights areas of Canada with the greatest potential for clastic-dominated zinc deposits. The preferred prospectivity model is based on public geological, geochemical, and geophysical datasets that were spatially indexed using the H3 discrete global grid system. Each H3 cell is associated with a prospectivity value, or class probability, calculated from the best-performing gradient boosting machines model. Model results are filtered to include the top 20% of prospectivity values for visualization purposes.

Prospectivity model highlights areas of Canada with the greatest potential for magmatic nickel deposits. The preferred prospectivity model is based on public geological, geochemical, and geophysical datasets that were spatially indexed using the H3 discrete global grid system. Each H3 cell is associated with a prospectivity value, or class probability, calculated from the best-performing gradient boosting machines model. Model results are filtered to include the top 20% of prospectivity values for visualization purposes.

A predictive model for Canadian carbonatite-hosted REE ± Nb deposits is presented herein. This model was developed by integrating diverse data layers derived from geophysical, geochronological, and geological sources. These layers represent the key components of carbonatite-hosted REE ± Nb mineral systems, including the source, transport mechanisms, geological traps, and preservation processes. Deep learning algorithms were employed to integrate these layers into a comprehensive predictive framework. Here is a link to the publication that describes this product: https://link.springer.com/article/10.1007/s11053-024-10369-7