We digitize the universe of original patent documents issued in England, Wales, Scotland, and Ireland between 1853 and 1900. Through state-of-the-art Optical Character Recognition techniques, data analysis using large language models, and manual verification, we construct a machine-readable database covering over 300,000 patent documents. The data includes information on the patent title, technological classification, issue and filing dates, the name of the inventor, their profession, and their address of residence, which we geocode to precise coordinates. This dataset represents a novel and unique resource to study the Second Industrial Revolution in the United Kingdom.

Between 1890 and 1924 more than four million Italians emigrated to the United States. During this period, Italy was the single largest supplier of emigrants in the world. This dataset tracks Italians who arrived in the Ellis Island immigration station between 1892 and 1924. We collect individual-level information on 3.6 million immigrants, including immigration year, literacy status, municipality of origin, and age. In ongoing work, we are leveraging census linking algorithms to merge the resulting dataset with individual-level historical (US) census data. This will yield a novel tool to study a broad set of questions concerning one of the defining immigrant group in (historical) American society.

Over the XIX and early XX century, approximately 4 million British immigrants settled in the United States. This project develops a new dataset which allows to link every migrant recorded in the US census to his entry in the UK census. To do so, we leverage individual confidential data from historical censuses recorded in both countries between 1850 and 1920 and state-of-the-art algorithms explicitly developed to link census data. We can thus reconstruct disaggregated bilateral migration flows between the UK and the US. The resulting dataset is a general-purpose novel tool available to social scientists which allows to study migration phenomena at an unrivalled level of detail.