data-modeling

To design a genealogy database schema that separates evidence from conclusions, model sources and citations independently from persons, relationships, and events. This source-first approach enforces an authored-vs-inferred persistence rule, ensuring research remains fully traceable and avoiding permanent mistakes.

To model uncertain genealogy dates in SQLite, implement a structured date model that explicitly captures exact, about, before, after, between, and unknown states. This uncertainty-safe modeling ensures date ambiguity is accurately represented rather than flattened into exact timestamps.

GEDCOM 5.5.1 alignment works with custom genealogy schemas by mapping internal entities for persons, relationships, and events to expected import/export structures. This includes evaluating GEDCOM-X vs GEDCOM 5.5.1 scenarios to ensure clean data interchange.

An authored-vs-inferred persistence rule in genealogy data modeling is a constraint requiring that only explicitly recorded evidence is stored, preventing inferred values from permanently overwriting database records. This keeps conclusion data distinct from source evidence.

To structure SQLite batch writes for genealogy data imports, apply performance-aware write guidance that handles junction tables and foreign keys efficiently. This approach manages complex relationship mappings and source citations without degrading database import speed.

Yes, you can generate an ERD for genealogy sources, citations, and media relationships. The schema design defines table relationships and foreign keys across persons, families, events, and media, ensuring proper junction-table modeling for complex many-to-many associations.