Creating a Historical Migration Dataset from Finnish Church Records, 1800-1920
This work provides a valuable dataset for studying historical demographic patterns like migration and urbanization in Finland, though it is incremental in applying existing methods to new archival data.
The researchers tackled the problem of extracting structured migration data from handwritten Finnish church records (1800-1920) by automating the process with a deep learning pipeline, resulting in a dataset of over six million entries from 200,000 images.
This article presents a large-scale effort to create a structured dataset of internal migration in Finland between 1800 and 1920 using digitized church moving records. These records, maintained by Evangelical-Lutheran parishes, document the migration of individuals and families and offer a valuable source for studying historical demographic patterns. The dataset includes over six million entries extracted from approximately 200,000 images of handwritten migration records. The data extraction process was automated using a deep learning pipeline that included layout analysis, table detection, cell classification, and handwriting recognition. The complete pipeline was applied to all images, resulting in a structured dataset suitable for research. The dataset can be used to study internal migration, urbanization, and family migration, and the spread of disease in preindustrial Finland. A case study from the Elimäki parish shows how local migration histories can be reconstructed. The work demonstrates how large volumes of handwritten archival material can be transformed into structured data to support historical and demographic research.