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Emotional Data Model v0.5.0 encodes emotional context in a stable format, suggesting advancements in AI systems.
The Emotional Data Model (EDM) v0.5.0 defines a governed, schema-bound representational architecture for encoding affective context as a stable, machine-interpretable data object. Unlike contemporary AI systems where emotional signals remain transient and architecture-bound, EDM externalises affective context into a domain-complete manifold comprising ten mandatory structural domains and 96 explicitly defined fields. The architecture achieves representational stability through explicit field definitions, in-band governance, and strict separation between representation, persistence, and computation layers. Artifacts are preserved within the .ddna envelope—a byte-stable container providing cryptographic integrity via W3C Data Integrity Proofs (eddsa-jcs-2022), sovereignty guarantees, and cross-vendor portability. v0.5.0 expands five canonical enumerations validated through systematic evaluation across three independent LLM providers, achieving 90%+ structural compliance, 77.3% narrative semantic similarity, and 56.5% cross-field semantic agreement. Identity binding is provided through VitaPass, a sovereign identity and consent infrastructure enabling portable, cross-vendor artifact recognition. EDM addresses the representational deficit in current intelligent systems by transforming implicit emotional states into explicit, rights-bearing data objects capable of surviving across model generations, computational paradigms, and regulatory environments.
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Jason Harvey (2026) studied this question.
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