The core object
The decision evidence record
The record is the whole point of ODES. It is not the raw data, not the model, not the full audit system, and not the workflow that produced the decision. It is a portable governance envelope for a decision: a structured evidence container that answers one relying-party question:
What was decided, by whom or by what, under whose authority, with what human disposition and machine role, against what evidence and policy basis, under what model state, and with what freshness?
Crucially, the record does not have to expose the evidence itself. It can carry references, hashes, attestations, verification material, policy identifiers, risk coordinates, freshness, revocation, and consumption conditions — so confidential material stays with the issuer while the relying party still gets structured evidence it can evaluate under its own rules.
Field vocabulary
What a record captures
A plain-English view of the governance coordinates a decision should carry when it crosses a boundary. The full field summary and schema profiles live in the repository.
Authority
The basis on which the decision could be made, and by whom.
Machine role
Whether AI retrieved, recommended, executed, or escalated.
Human disposition
Whether a human reviewed, modified, overrode, or simply accepted.
Model state
Version, tool access, and runtime conditions that shaped the output.
Evidence & policy basis
References, hashes, and policy identifiers — not the raw evidence.
Freshness
Expiration, revocation, supersession, and consumption conditions.
Verification
Structure is not reliance
One of the most important distinctions in ODES: a well-formed record is not the same as a trusted one. Each layer means something different.
Where it fits
Complementary, not winner-take-all
ODES sits between the tools you already have. It's the portable decision-evidence layer that lets them interoperate across a boundary.
ISO 42001, NIST AI RMF
Related work
Boundary blindness
ODES is informed by adjacent work on provenance, AI governance, model documentation, and decision traceability. Alexander D. Barrett’s July 2026 paper, Boundary Blindness Under Artificial Intelligence, is especially important related work because it frames the problem as a cross-boundary decision-evidence gap that AI accelerates rather than creates. ODES should be read as one candidate standards-layer response to that diagnosis. No endorsement, affiliation, sponsorship, or relationship is implied.
Status
An open, early draft
v0.2 · discussion draft
ODES is a candidate open standard, not a finished specification. The strong claim is narrow: ODES defines the portable decision-evidence record as the interoperability object for AI-influenced decisions that cross boundaries. It addresses the part that governance frameworks, model documentation, provenance systems, and audit trails often leave under-specified.
It is developed in the open and meant to be shaped by the people who would issue, verify, and rely on these records. The discussion draft, schema profiles, examples, and field summary are maintained in the public repository.