The author of the text, a Head of Product Innovation & Developer Strategy at Neo4j, shares their experience importing GEDCOM files into Neo4j to explore genealogy and ancestry data as a graph. They used a tool that queries GEDCOM files with a syntax similar to JSON, allowing them to extract individual attributes and relationships. The author then used the Python library `python-gedcom` to parse and query the GEDCOM file, creating a dataset for the British Royals and US Presidents. They pre-processed the data by extracting specific attributes and filtering out individuals without parents of the current type. The authors then imported the data into Neo4j using the Neo4j AuraDB Free instance, creating nodes for each person with their attributes and relationships. To add more complexity to the graph, they added inferred relationships such as family ties, sibling relationships, and ancestral relationships. They also explored visualization options in Neo4j Browser and Bloom, discovering a beautiful graph visualization of the ancestry data. The authors provide code examples using Python and Cypher queries to create the data model and import it into Neo4j, highlighting potential issues with uniqueness checks due to non-unique IDs within GEDCOM files.