The dataset consists of the input data, parameters, and results output from mineral resource assessment calculations.

A mineral resource assessment for tungsten, a critical mineral commodity (see the critical mineral list published by Fortier and others, 2018) for the United States, was carried out by the U.S. Geological Survey (USGS) for a portion of the Great Basin region, in western Nevada and eastern California, between latitudes 36N and 42N and longitudes 116W and 120W. This study (Lederer and others, in review) integrates data from several sources, including geologic, geochemical, geophysical, remote sensing, watershed analysis, and mining with recently developed grade and tonnage models, expert estimates, and software tools and analyses to generate probabilistic estimates of undiscovered tungsten skarn resources. The assessment was conducted following the 3-part assessment methodology developed by Singer and Menzie (2010), which involved the delineation of permissive tracts, as well as the evaluation of interdisciplinary data that were then presented to a panel of experts, who made estimations that were then analyzed using economic filters. These data are presented in several formats: a GIS geodatabase, shapefiles, and tabular (csv) data. Several layers or individual files are derived or contain data from U.S. Geological Survey (USGS) and other existing, published sources, mainly the USGS National Geochemical Database (NGDB), USGS Mineral Resources Data System (MRDS), and the National Uranium Resource Evaluation (NURE) databases.

The dataset consists of the input data, parameters, and results output from mineral resource assessment calculations.

A mineral resource assessment for tungsten, a critical mineral commodity (see the critical mineral list published by Fortier and others, 2018) for the United States, was carried out by the U.S. Geological Survey (USGS) for a portion of the Great Basin region, in western Nevada and eastern California, between latitudes 36N and 42N and longitudes 116W and 120W. This study (Lederer and others, in review) integrates data from several sources, including geologic, geochemical, geophysical, remote sensing, watershed analysis, and mining with recently developed grade and tonnage models, expert estimates, and software tools and analyses to generate probabilistic estimates of undiscovered tungsten skarn resources. The assessment was conducted following the 3-part assessment methodology developed by Singer and Menzie (2010), which involved the delineation of permissive tracts, as well as the evaluation of interdisciplinary data that were then presented to a panel of experts, who made estimations that were then analyzed using economic filters. These data are presented in several formats: a GIS geodatabase, shapefiles, and tabular (csv) data. Several layers or individual files are derived or contain data from U.S. Geological Survey (USGS) and other existing, published sources, mainly the USGS National Geochemical Database (NGDB), USGS Mineral Resources Data System (MRDS), and the National Uranium Resource Evaluation (NURE) databases.

The data release includes GIS data that map potential for tungsten skarn mineralization in permissive tracts in the Yukon-Tanana Uplands, Eastern Alaska, along with tables listing keywords and procedures used to produce the permissive tracts and score them for mineral potential.The GIS data are encapsulated in a file geodatabase called "AK_Wskarn_tract.gdb" and are also available in the shapefile and KMZ formats. The geodatabase contains three datasets. The polygon feature class "primary_attributes" contains the scored tungsten skarn permissive tract subdivided by National Hydrography Dataset HUC12 drainages. A related table, "qualitative_assessment" contains detailed scoring information for each feature. The point feature class "mineral_sites_ranked" contains W (tungsten) bearing mineral sites pulled from the Alaska Resource Data File with additional fields added for this study. The GIS data folder also includes the Python script used to score potential.

This data release supports the paper titled, “Tungsten skarn potential of the Yukon-Tanana Uplands, Eastern Alaska, USA-A mineral resource assessment”, published via open-access license in the Journal of Geochemical Exploration and available at: https://doi.org/10.1016/j.gexplo.2020.106700. The data release includes GIS data that map potential for tungsten skarn mineralization in permissive tracts in the Yukon-Tanana Uplands, Eastern Alaska, along with tables listing keywords and procedures used to produce the permissive tracts and score them for mineral potential. Supplementary Data part A lists keywords used to extract permissive rock types from the Geologic Map of Alaska (Wilson et al., 2015) to generate the permissive tract for tungsten skarn. Supplementary Data part B describes the tract polishing procedures. Supplementary Data part C lists the parameters for scoring tungsten skarn mineralization potential within the permissive tract features. The GIS data are encapsulated in a file geodatabase called AK_Wskarn_tract.gdb and are also available in the shapefile and KML formats. The geodatabase contains three datasets. The polygon feature class “primary_attributes” contains the scored tungsten skarn permissive tract subdivided by National Hydrography Dataset HUC12 drainages. A related table, “qualitative_assessment” contains detailed scoring information for each feature. The point feature class “mineral_sites_ranked” contains W-bearing mineral sites pulled from the Alaska Resource Data File with additional fields added for this study. The GIS data folder also includes the Python script used to score potential. The datasets and methods are described in detail in the accompanying paper.

The .csv table is part of a dataset package that was compiled for use as mineral assessment guidance in the Sagebrush Mineral-Resource Assessment project (SaMiRA). Mineral potential maps from previous mineral-resource assessments which included areas of the SaMiRA project areas were georeferenced. The images were clipped to the extent of the map and all explanatory text, gathered from map explanations or report text, was recorded into this table. This table is to be used in conjunction with the individual georeferenced raster images. It includes the image file name, map title and figure caption when appropriate. The images are also classified according to the legal definition of mineral resources: metallic, non-metallic, leasable non-fuel, leasable fuel, geothermal, paleontological, and saleable.

The .csv table is part of a dataset package that was compiled for use as mineral assessment guidance in the Sagebrush Mineral-Resource Assessment project (SaMiRA). Mineral potential maps from previous mineral-resource assessments which included areas of the SaMiRA project areas were georeferenced. The images were clipped to the extent of the map and all explanatory text, gathered from map explanations or report text, was recorded into this table. This table is to be used in conjunction with the individual georeferenced raster images. It includes the image file name, map title and figure caption when appropriate. The images are also classified according to the legal definition of mineral resources: metallic, non-metallic, leasable non-fuel, leasable fuel, geothermal, paleontological, and saleable.