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 data product is currently under evaluation and review. It may contain inaccuracies or be subject to change. Users should exercise caution and discretion when interpreting or relying on this information. The government assumes no liability for any errors or decisions based on this preliminary data. For more details, please see the Government of Canada's Open Commons license (https://open.canada.ca/en/open-government-licence-canada). The Canadian Soil Information Service has developed a detailed dataset of Canada's soils and associated properties using advanced machine learning techniques. The Soil Landscape Grids of Canada is produced using a combination of historical and current data from both soil sampling and remote sensing. The machine learning model is trained using over 10,000 pedon locations from across Canada as well as 70 covariate datasets. This new dataset is pivotal in addressing the gaps left by legacy soil surveys and facilitates more comprehensive assessments nationwide. As new data becomes available and machine learning techniques advance, this information can be updated much faster than with traditional soil surveying methods.

The Essential Skills Playbook projects map is developed to highlight projects featured as part of the “Essential Skills Playbook” published by the Office of Literacy and Essential Skills program (OLES) at Employment and Social Development Canada (ESDC). The playbook is developed as a showcase for sharing promising practices, case studies and partnerships, based on OLES projects that were funded through grants and contributions generally dating back to 2012. This map allows users to visualize OLES-funded projects and explore various data variables such as the targeted groups, essential skills, and industry sectors of each project.

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.

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

Dataset of building footprints in the Yukon Territory. Building footprints were extracted from LiDAR orthophotos using deep learning. Manual corrections were applied to both erroneous and missed building extractions. The Regularize Building Footprint tool was used to reduce vertices and simplify the footprints. A tolerance of 1 was used, with a precision of 0.25.Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps). Discover more digital map data and interactive maps from Yukon’s digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)

This service shows the percentage of population, excluding institutional residents, with knowledge of English and French for Canada by 2016 census division. The data is from the Census Profile, Statistics Canada Catalogue no. 98-316-X2016001.Knowledge of official languages refers to whether the person can conduct a conversation in English only, French only, in both languages or in neither language. For a child who has not yet learned to speak, this includes languages that the child is learning to speak at home. For additional information refer to 'Knowledge of official languages' in the 2016 Census Dictionary.For additional information refer to 'Knowledge of official languages' in the 2016 Census Dictionary.To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census division” web service, accessible in the data resources section below.

This service shows the percentage of population, excluding institutional residents, with knowledge of English and French for Canada by 2016 census subdivision. The data is from the Census Profile, Statistics Canada Catalogue no. 98-316-X2016001.Knowledge of official languages refers to whether the person can conduct a conversation in English only, French only, in both languages or in neither language. For a child who has not yet learned to speak, this includes languages that the child is learning to speak at home. For additional information refer to 'Knowledge of official languages' in the 2016 Census Dictionary.For additional information refer to 'Knowledge of official languages' in the 2016 Census Dictionary.To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census subdivision” web service, accessible in the data resources section below.

Trails designed for hiking.attribut:ID - Unique identifier**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

This is an approximated visualization of the School Authority Unorganized information that is currently available on the Alberta Education public website (https://education.alberta.ca/boundary-maps/school-jurisdiction-maps/everyone/view-and-print-maps). The information has been informed by Ministerial Orders and is presented in a mapping format.