Compilation of open asset-level data, as of Dec 2022

This dataset is a compilation of open asset-level data, which means the location of sites (e.g., operation, manufacturing, processing facilities of global supply chains), as of December 2022. This included data from 9 publicly available sources, that after data cleaning and harmonization, resulted in 189,075 data points. <strong>Data source</strong> <strong>Number of data points</strong> Open Supply Hub (former Open Apparel Registry) 96,736 Global Power Plant Database 35,419 Climate trace 19,945 FDA database 12,898 Global Dam Watch 11,017 EudraGMDP database 5,181 Sustainable Finance Initiative GeoAsset Databases 4,716 Global Tailings Portal 1,956 Fine print Mining Database 1,207 This data was assigned with the industry in which the asset is. The summary table below shows the number of assets by industry. <strong>Industry</strong> <strong>Number of assets </strong> Textiles, Apparel &amp; Luxury Good Production 96,736 Health Care, Pharma and Biotechnology 18,079 Energy - Solar, Wind 16,282 Energy - Hydropower 14,515 Energy - Geothermal or Combustion 11,724 Metals &amp; Mining 11,210 Transportation Services 4,872 Construction Materials 3,117 Agriculture (animal products) 2,388 Agriculture (plant products) 1,896 Oil, Gas &amp; Consumable Fuels 1,194 Water utilities / Water Service Providers 892 Hospitality Services 294 Fishing and aquaculture 14 Other 5,862 <strong>Note that this compilation is based on an extensive search, however, we acknowledge that there is a significant discrepancy in data coverage/comprehensiveness among the different industries.</strong> The industry "Textiles, Apparel &amp; Luxury Good Production" is by far the most complete, while other are clearly far from complete, for example, “Construction Materials”, "Agriculture (animal products)”, “Agriculture (plant products)”, “Oil, Gas &amp; Consumable Fuels”, “Water utilities / Water Service Providers”, “Hospitality Services”, “Fishing and aquaculture”. <strong>Therefore, any comparison between industries should take this coverage/comprehensiveness bias into consideration.</strong>