Full methodology, all discoveries, complete tech stack documented here (LinkedIn article, sorry, but it's where I published it):

www.linkedin.com/pulse/follow...

Methodology works for any adapted literary work, museum collection or cultural dataset.

#DigitalHumanities #KnowledgeGraphs #LinkedData

Also built the wrong graph first (casting database instead of thematic analysis) and had AI generate completely incorrect Wikidata QIDs.

My Scarecrow: a river in Italy 🤦
My Wicked Witch: a German municipality

Verification matters.

Built it with free tools: Wikidata (SPARQL), VIAF/ISNI, TMDB, Neo4j.

Used Claude to help write Python scripts (I can't code).

The secret: Persistent Identifiers. When your data sources have PIDs, everything connects almost magically.

The graph revealed patterns I'd never have found through traditional reading:

• Dorothy in The Wiz (1978) is a 24-year-old teacher, not a child—reflects post-Civil Rights focus on adult self-determination vs. childhood nostalgia

• "Good vs Evil" completely inverts from 1939 to Wicked 2024

There’s MARC21, Unimarc, Pica3, Pica+, Intermarc I know of - and these are widely used in Western Europe (excluding local variants of these variants), and I believe Eastern Europe has again its own Marc standards.