Compilation of open asset-level data, as of Dec 2022
Description
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.
| Data source | Number of data points |
| 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.
| Industry | Number of assets |
| Textiles, Apparel & 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 & Mining | 11,210 |
| Transportation Services | 4,872 |
| Construction Materials | 3,117 |
| Agriculture (animal products) | 2,388 |
| Agriculture (plant products) | 1,896 |
| Oil, Gas & Consumable Fuels | 1,194 |
| Water utilities / Water Service Providers | 892 |
| Hospitality Services | 294 |
| Fishing and aquaculture | 14 |
| Other | 5,862 |
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. The industry "Textiles, Apparel & 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 & Consumable Fuels”, “Water utilities / Water Service Providers”, “Hospitality Services”, “Fishing and aquaculture”. Therefore, any comparison between industries should take this coverage/comprehensiveness bias into consideration.