automated-extraction-of-techno-economic-data-from-76-000-energy-system-studies-0bd6d5d5·1 events·first seen Aliases: Automated Extraction of Techno-Economic Data from 76,000 Energy System Studies
Researchers demonstrate automated extraction of quantitative techno-economic data from 76,000 energy system studies published since 2010, producing a FAIR database of 3.2 million structured data points and 20 million metadata entries. The system enables meta-analysis of the energy systems literature at scale, revealing where academic modeling assumptions diverge from empirical data. The work is a large-scale applied NLP/information-extraction deployment in a high-stakes scientific domain, with the resulting database made publicly accessible via an interactive dashboard.