Skip to content

Research at St Andrews

Probabilistic linkage of vital event records in Scotland using familial groups

Research output: Contribution to conferenceAbstract


School/Research organisations


We report on the assembly of longitudinal data from Scottish birth, death and marriage records representing eighteen million individuals. An experimental approach based on familial groups starts by gathering parents and their siblings into bundles with the aim of (as near of possible) partitioning the certificates into familial groups. This may be achieved by bundling marriage and birth certificates according to a signature derived from their attributes. This is similar to but different from blocking used in most entity resolution schemes where certificates of one kind are gathered together. We have experimented with these techniques using hand coded data from an historic Scottish dataset as a gold standard for comparison. In this paper we will report on our techniques and some preliminary results from our experiments.


Original languageEnglish
Publication statusPublished - 11 May 2017
EventWorkshop for the Systematic Linking of Historical Records - University of Guelph, Guelph, Canada
Duration: 11 May 201713 May 2017


WorkshopWorkshop for the Systematic Linking of Historical Records
Internet address

    Research areas

  • record linkage

Discover related content
Find related publications, people, projects and more using interactive charts.

View graph of relations

Related by author

  1. Linking Scottish vital event records using family groups

    Akgün, Ö., Dearle, A., Kirby, G. N. C., Garrett, E., Dalton, T. S., Christen, P., Dibben, C. J. L. & Williamson, L. E. P., 25 Mar 2019, In : Historical Methods: a Journal of Quantitative and Interdisciplinary History. Latest articles, 17 p.

    Research output: Contribution to journalArticle

  2. Record linking using metric space similarity search

    Dearle, A., Kirby, G. N. C., Akgun, O. & Dalton, T. S., 2 Apr 2017.

    Research output: Contribution to conferenceAbstract

  3. Evaluating population data linkage: assessing stability, scalability, resilience and robustness across many data sets for comprehensive linkage evaluation

    Dalton, T. S., Akgun, O., Al-Sediqi, A., Christen, P., Dearle, A., Garrett, E., Gray, A., Kirby, G. N. C. & Reid, A., 2 Apr 2017.

    Research output: Contribution to conferenceAbstract

ID: 250035825