KNOWLEDGE DATABASE FOR HISTORICAL DEMOGRAPHY

Pascal Chareille, University of Tours
Alain Bouju, La Rochelle University
Mickaël Coustaty, La Rochelle University
Isabelle Seguy, INED
Arnaud Bringe, Institut National d'Études Démographiques (INED)
Doriane Hare, CNRS
François-Joseph Ruggiu, Sorbonne University
Vincent Gourdon, Centre National de la Recherche Scientifique (CNRS)
Isabelle Robin, Sorbonne University
Antoine Doucet, La Rochelle University
Jerome Galichon, Geneanet
Christopher Kermorvant, Teklia, Paris and Laboratoire LITIS, Université de Rouen
Solene Tarride, Teklia
Alienor Samuel-Herve, Geneanet

We use digitized historical material (parish and civil registers) to extract data using some Handwritten Text Recognition tools and store them in a knowledge base. We have gathered multiple datasets from various sources, all of which share common conceptual frameworks despite using different data formats. Our approach will enable us to process both manually transcribed data and data extracted using handwriting recognition. This will allow us to expand our datasets to further content that will aggregated all over the project duration. This paper presents the overall architecture of our proposed system, which is centered around a semantic web-based knowledge base. It also outlines the structural elements that will be used to guide handwriting recognition and to organize data within our knowledge base. This project has the potential to significantly advance research in historical demography by providing a comprehensive and accessible knowledge base.

Keywords: Historical Demography, Data and Methods, Digital and computational demography, Families, Unions and Households

See paper.