Canon as Repository: A Specification-Driven Architecture for Transmedia Intellectual Property

Creative intellectual property management is the conspicuous exception among mature domains of complex designed systems: engineering, medicine, software, and scientific publishing have each independently developed formal mechanisms to verify that artifacts satisfy their specifications; creative IP has not. Transmedia franchises accumulate contradictions as intellectual property is rendered across novels, films, games, and merchandise because no formal specification governs what the story is independently of how it is expressed. Building on transmedia storytelling theory (Dena, 2009; Jenkins, 2006, 2011; Ryan, 2001, 2015), world-building research (Wolf, 2012), and the rendering problem framework (Zharnikov, 2026), this paper proposes a specification-driven architecture to close the gap. The canonical specification is reconceived as a version-controlled repository: editions are tagged commits; translations and adaptations are forks; canon governance operates through pull requests; and consistency validation functions as continuous integration. Style is a rendering parameter rather than a property of the specification; actors and translators function as rendering operators; and artificial intelligence clarifies the authorship question by distinguishing specification (the creative act) from rendering (the craft act). Seven testable propositions address franchise consistency, IP licensing as fork governance, and a future in which audiences become renderers – generating personalized expressions from a published canonical specification. Includes zharnikov-2026w-canon-as-repository.yaml (Paper Spec v0.1.0) – a machine-readable specification of the paper's claims, assumptions, and dependencies. The paper's full machine-first bundle (the SPINE claim/dependency graph and the ONTOLOGY term module) lives in the public repository; see https://github.com/spectralbranding/paper-spec for the standard. This PDF is generated programmatically from that machine-first source under a research-as-repository model.