AncestryAI is an application which uses machine learning to infer family trees and enables visualizing and searching the inferred trees. It has been developed to support genealogical research and to provide material for studies in computational social science, demography, and other disciplines.

News

(2018-03-24) A new version of AncestryAI with several improvements has been released.

Technical requirements

Only Chrome and Firefox browsers are currently supported.

Material

The family trees are inferred from about 5 million birth records from Finland collected by the HisKi project. The records cover years from the mid-1600's to mid-1800's and partly to the early 20th century. The coverage of the records was originally close to full, but the digitized material covers only parts of the complete dataset (some material is not digitized yet, and some is lost).

Usage instructions

You can start by searching for an individual in the upper-right panel and clicking one of the search results which opens the person in the Tree view (on the left). Clicking a person in the Tree view opens his or her family and brings the person's information to the Info view (lower-right). The Info view also displays the most probable parents of the selected person.

You can add and remove sub views from the plus and minus bars next to the borders and adjust their sizes from the middle bars. The tree view can be zoomed in and out using the mouse wheel.

NB: When building your family tree, you should verify the links inferred by the algorithm by studying the original parish records. However, with AncestryAI the process can be made more efficient since you can start from the most probable parent candidates.

Known issues

Nodes in the Tree view cannot be moved. Individuals without a family name are currently not linked. The algorithm doesn't consider patronyms.

Source code

The source code is available on GitHub under the MIT Licence. Contributions are welcome.

Algorithm

The family links are inferred based on the names, birth dates, and birth locations of the individuals using a probabilistic machine-learning approach. For more information, see our papers Computationally Inferred Genealogical Networks Uncover Long-Term Trends in Assortative Mating and AncestryAI: A Tool for Exploring Computationally Inferred Family Trees.

Creators

AncestryAI is maintained by Eric Malmi, who is developing collective entity resolution methods for genealogical data in his PhD project. The web application has been originally implemented by Marko Rasa.

All feedback is welcome at: eric.malmi@gmail.com