Reconstructing Historical Populations from Genealogical Data Files

  • Corry GellatlyEmail author


Over the past two decades, a huge number of historical documents have been digitised and made available online. At the same time, numerous software options and websites have encouraged people to conduct research into their family trees, leading to a surge in the availability of genealogical data. A major advantage of genealogical data, from a scientific research perspective, is that it combines information from many sources into a format that is structured by family relations and descendancy, which is very useful for studying the dynamics of population change over the generations. A critical issue for researchers who want to use genealogical data is how to assess the quality of the data and put in place measures to correct the errors that we find in it. In this chapter, I present some of the methods that are being used to filter, clean and aggregate genealogical data to create large datasets that may be used across a diverse range of academic research disciplines.


Data Coverage Potential Error Family Tree False Match Early Modern Period 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Bhattacharya, I., & Getoor, L. (2007). Query-time entity resolution. Journal of Artificial Intelligence Research, 30, 621–657.Google Scholar
  2. Christen, P. (2012). Data matching. Berlin: Springer. doi: 10.1007/978-3-642-31164-2
  3. Fu, Z., Christen, P., & Boot, M. (2011). A supervised learning and group linking method for historical census household linkage. In Proceedings of the Ninth Australasian Data Mining Conference (Vol. 121, pp. 153–162). Australian Computer Society, Inc.Google Scholar
  4. Gavrilov, L. A. & Gavrilova, N. S. (2001). Biodemographic Study of Familial Determinants of Human Longevity. Population: An English Selection, 13(1), 197–221.Google Scholar
  5. Gavrilova, N. S., & Gavrilov, L. A. (2007). Search for predictors of exceptional human longevity. North American Actuarial Journal, 11(1), 49–67. doi: 10.1080/10920277.2007.10597437
  6. Gellatly, C. (2009). Trends in population sex ratios may be explained by changes in the frequencies of polymorphic alleles of a sex ratio gene. Evolutionary Biology, 36(2), 190–200. doi: 10.1007/s11692-008-9046-3
  7. Ivie, S., Pixton, B., & Giraud-Carrier, C. (2007). Metric-based data mining model for genealogical record linkage. In IRI 2007, IEEE international Conference on Infomation Reuse and Integration. Google Scholar
  8. Larmuseau, M. H. D., Van Geystelen, A., van Oven, M., & Decorte, R. (2013). Genetic genealogy comes of age: Perspectives on the use of deep-rooted pedigrees in human population genetics. American Journal of Physical Anthropology, 150(4), 505–511. doi: 10.1002/ajpa.22233
  9. Moreau, C., Bhérer, C., Vézina, H., Jomphe, M., Labuda, D., & Excoffier, L. (2011). Deep human genealogies reveal a selective advantage to be on an expanding wave front. Science, 334(6059), 1148–1150. doi: 10.1126/science.1212880
  10. Newcombe, H. B., Kennedy, J. M., Axford, S. J., & James, A. P. (1959). Automatic linkage of vital records: Computers can be used to extract “follow-up” statistics of families from files of routine records. Science, 130(3381), 954–959. doi: 10.1126/science.130.3381.954
  11. Otterstrom, S. M., & Bunker, B. E. (2013). Genealogy, migration, and the intertwined geographies of personal pasts. Annals of the Association of American Geographers, 103(3), 544–569. doi: 10.1080/00045608.2012.700607
  12. Post, W., van Poppel, F., van Imhoff, E., & Kruse, E. (1997). Reconstructing the extended kin-network in the Netherlands with genealogical data: methods, problems, and results. Population Studies, 51(3), 263–278. doi: 10.1080/0032472031000150046
  13. United Nations. (1983). Manual X: Indirect techniques for demographic estimation. United Nations Publication.Google Scholar
  14. Zhao, Z. (1994). Demographic conditions and multi-generation households in Chinese history. Results from genealogical research and microsimulation. Population Studies, 48(3), 413–425. doi: 10.1080/0032472031000147946

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of History and Art History Utrecht UniversityUtrechtThe Netherlands

Personalised recommendations