Documentation / Schemas

Illustrative structures for state and provenance.

These examples make the public concepts concrete. They are documentation examples, not a stable package, deployed database schema, or production contract.

Lifecycle event

MVP MOCK

type LifecycleEvent = {
  eventId: string;
  subjectType: "participant" | "asset" | "document" | "workflow";
  subjectId: string;
  eventType: string;
  occurredAt: string;
  source: EvidenceReference;
  state: "illustrative" | "recorded";
};

type EvidenceReference = {
  referenceId: string;
  sourceType: string;
  digest?: string;
  classification: "synthetic" | "external-reference";
};

The model emphasizes subject, event, source, and classification. Production schemas will require versioning, privacy analysis, authorization, validation, retention, and migration rules.

Schema principles

Prefer references over sensitive source payloads.
Separate observed evidence from legal or regulated conclusions.
Version records and events explicitly.
Preserve source and responsibility metadata.
Make synthetic versus external information unambiguous.