Reconstructing Historical Populations from Genealogical Data Files

Publication date

2015

Authors

Gellatly, C.ISNI 0000000426920219

Editors

Bloothooft, Gerrit
Peter, Christen
Mandemakers, Kees
Schraagen, Marijn

Advisors

Supervisors

Document Type

Part of book
Open Access logo

License

taverne

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Over the past two decades, a huge number of historical documents have been digitised and made available online.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

Taverne

Citation

Gellatly, C 2015, Reconstructing Historical Populations from Genealogical Data Files. in G Bloothooft, C Peter, K Mandemakers & M Schraagen (eds), Population Reconstruction. Springer, pp. 111-128. https://doi.org/10.1007/978-3-319-19884-2_6