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Reconstructing Historical Populations from Genealogical Data Files

  • Corry GellatlyEmail author
Chapter

Abstract

Over the past two decades, a huge number of historical documents have been digitised and made available online.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.

Keywords

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.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

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

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