Training and validation data from the AI for Critical Mineral Assessment Competition (ver. 2.0, July 2025)

Extracting useful and accurate information from scanned geologic and other earth science maps is a time-consuming and laborious process involving manual human effort. To address this limitation, the USGS partnered with the Defense Advanced Research Projects Agency (DARPA) to run the AI for Critical Mineral Assessment Competition, soliciting innovative solutions for automatically georeferencing and extracting features from maps. The competition opened for registration in August 2022 and concluded in December 2022. Training, validation, and evaluation data from the competition are provided here, as well as competition details and baseline solutions. The data are derived from published sources and are provided to the public to support continued development of automated georeferencing and feature extraction tools. References for all maps are included with the data. First Posted - December 27, 2023 Revised - July 21, 2025

Data and Resources

Field Value
accessLevel public
bureauCode {010:12}
catalog_@context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
catalog_@id https://ddi.doi.gov/usgs-data.json
catalog_conformsTo https://project-open-data.cio.gov/v1.1/schema
catalog_describedBy https://project-open-data.cio.gov/v1.1/schema/catalog.json
identifier http://datainventory.doi.gov/id/dataset/usgs-63a100d6d34e0de3a1f2794f
metadata_type geospatial
modified 2025-07-25T00:00:00Z
old-spatial -178.2, 6.6, -49.0, 83.3
publisher U.S. Geological Survey
resource-type Dataset
source_datajson_identifier true
source_hash ad19227e648e9da7d717d9f2b35ab560ba42415dca49695bf583f77f26208fd6
source_schema_version 1.1
spatial {"type": "Polygon", "coordinates": [[[-178.2, 6.6], [-178.2, 83.3], [ -49.0, 83.3], [ -49.0, 6.6], [-178.2, 6.6]]]}
theme {geospatial}
Groups
  • AmeriGEOSS
  • National Provider
  • North America
Tags
  • AmeriGEO
  • AmeriGEOSS
  • CKAN
  • GEO
  • GEOSS
  • National
  • North America
  • United States
  • ai
  • artificial-intelligence
  • competition
  • critical-mineral-resources
  • digitization
  • economy
  • geological-maps
  • geoscientificinformation
  • geospatial-datasets
  • gis
  • machine-learning
  • ml
  • modeling
  • resource-assessment
  • tool-development
  • topographic-maps
  • training-data
  • usgs-63a100d6d34e0de3a1f2794f
isopen False
license_id notspecified
license_title License not specified
maintainer Margaret A Goldman
maintainer_email mgoldman@usgs.gov
metadata_created 2025-09-24T18:48:40.460303
metadata_modified 2025-09-24T18:48:40.460313
notes Extracting useful and accurate information from scanned geologic and other earth science maps is a time-consuming and laborious process involving manual human effort. To address this limitation, the USGS partnered with the Defense Advanced Research Projects Agency (DARPA) to run the AI for Critical Mineral Assessment Competition, soliciting innovative solutions for automatically georeferencing and extracting features from maps. The competition opened for registration in August 2022 and concluded in December 2022. Training, validation, and evaluation data from the competition are provided here, as well as competition details and baseline solutions. The data are derived from published sources and are provided to the public to support continued development of automated georeferencing and feature extraction tools. References for all maps are included with the data. First Posted - December 27, 2023 Revised - July 21, 2025
num_resources 2
num_tags 26
title Training and validation data from the AI for Critical Mineral Assessment Competition (ver. 2.0, July 2025)