A public, browsable knowledge graph reconciling Taiwanese tea cultivar genetics — scattered across peer-reviewed molecular studies, institutional breeding records, and conflicting vernacular naming — into one queryable structure.
Purpose
Tea in Taiwan spans three genetically and historically distinct lineages: the wild endemic species Camellia formosensis, introduced/naturalized Assamica-type "ancestor trees," and cultivars bred since 1903 by the Tea Research and Extension Station (TRES). The underlying genetics are well-studied, but the data is fragmented — inconsistent identifiers across molecular studies, unstructured institutional web pages, and the same cultivar going by multiple non-interchangeable names and codes. Nobody has reconciled it into a single, internally consistent, machine-queryable structure. That reconciliation — not the tea itself — is the informatics contribution.
What it will do
Named tea-growing regions across Taiwan, browsable with no genetics or graph-database background required.
A searchable, visual view of how today's commercial cultivars trace back to wild or historically introduced ancestors — e.g. TTES No. 18 ("Ruby Red"), a literal genetic bridge between the wild endemic species and an Assamica variety from Burma.
How it's being built
Cultivar and species records are extracted from primary literature and institutional sources, then resolved into a canonical entity model — recognizing when records using different identifiers refer to the same real-world cultivar — with full source provenance retained on every claim.
Resolved entities are loaded into a Neo4j property graph, queried with Cypher, so questions like "which currently cultivated teas trace back to the wild endemic species" can be answered directly through graph traversal instead of a different table-join query for every possible path.
Built MVP-first: a small, genuinely working product covering a few cultivars and regions ships early, then grows incrementally — rather than waiting for "complete" data in a domain that has no natural stopping point.
Stack
Neo4jCypherPythonpandasDuckDBEntity ResolutionStatus
Early-stage and actively evolving. Literature capture and note synthesis are underway; the Neo4j graph and public web app aren't built yet — but the reasoning, sources, and workflow are all public now.