Dataset Viewer
Duplicate
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
algorithm: string
name: string
version: string
description: string
rules: list<item: string>
  child 0, item: string
signing_prefix: string
example_input: struct<z: int64, a: string, m: null>
  child 0, z: int64
  child 1, a: string
  child 2, m: null
example_canonical: string
anchoring: string
signing_algorithm: string
record_types: list<item: struct<type: string, name: string, description: string, required_fields: list<item: strin (... 40 chars omitted)
  child 0, item: struct<type: string, name: string, description: string, required_fields: list<item: string>, subject (... 28 chars omitted)
      child 0, type: string
      child 1, name: string
      child 2, description: string
      child 3, required_fields: list<item: string>
          child 0, item: string
      child 4, subject_fields: list<item: string>
          child 0, item: string
spec_version: string
hash_algorithm: string
canonicalization: string
to
{'spec_version': Value('string'), 'record_types': List({'type': Value('string'), 'name': Value('string'), 'description': Value('string'), 'required_fields': List(Value('string')), 'subject_fields': List(Value('string'))}), 'canonicalization': Value('string'), 'signing_algorithm': Value('string'), 'hash_algorithm': Value('string'), 'anchoring': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 299, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              algorithm: string
              name: string
              version: string
              description: string
              rules: list<item: string>
                child 0, item: string
              signing_prefix: string
              example_input: struct<z: int64, a: string, m: null>
                child 0, z: int64
                child 1, a: string
                child 2, m: null
              example_canonical: string
              anchoring: string
              signing_algorithm: string
              record_types: list<item: struct<type: string, name: string, description: string, required_fields: list<item: strin (... 40 chars omitted)
                child 0, item: struct<type: string, name: string, description: string, required_fields: list<item: string>, subject (... 28 chars omitted)
                    child 0, type: string
                    child 1, name: string
                    child 2, description: string
                    child 3, required_fields: list<item: string>
                        child 0, item: string
                    child 4, subject_fields: list<item: string>
                        child 0, item: string
              spec_version: string
              hash_algorithm: string
              canonicalization: string
              to
              {'spec_version': Value('string'), 'record_types': List({'type': Value('string'), 'name': Value('string'), 'description': Value('string'), 'required_fields': List(Value('string')), 'subject_fields': List(Value('string'))}), 'canonicalization': Value('string'), 'signing_algorithm': Value('string'), 'hash_algorithm': Value('string'), 'anchoring': Value('string')}
              because column names don't match

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

AXIOM Envelope Specification

AXIOM (Audit eXtensible Input/Output Manifest) is the canonical envelope format used by Crovia for packaging tamper-evident AI audit records.

Design goals

  • Tamper-evident: each envelope contains a hash of its content and is included in a Merkle chain
  • Offline-verifiable: all verification can be performed without contacting Crovia servers
  • Extensible: supports multiple record types (AX.NEC, AX.OBS, AX.TPA, AX.CEP)
  • Anchored: the Merkle root of each ledger batch is anchored to Bitcoin via OpenTimestamps

Envelope structure

{
  "ax_id": "AX-<example-id>",
  "ax_type": "AX.OBS",
  "issued_at": "2026-01-01T00:00:00Z",
  "subject": {
    "model_id": "<vendor>/<model>",
    "observation_type": "omission",
    "severity": "high"
  },
  "content_hash": "sha256:<example-hash>",
  "prev_hash": "sha256:<example-prev-hash>",
  "merkle_root": "sha256:<example-merkle-root>",
  "signature": "Ed25519:<example-signature>"
}

Record types

Type Description
AX.NEC Non-disclosure / omission records from Necessary Evidence Chain
AX.OBS Observation records from forensic analysis
AX.TPA Temporal Provenance Attestations
AX.CEP Canonical Evidence Packages

Canonicalization

AXIOM uses CSC-1 (Crovia Standard Canonicalization 1): deterministic JSON serialization with lexicographically sorted keys, no whitespace. Used as the input to Ed25519 signing.

Anchoring

Weekly Merkle roots are submitted to OpenTimestamps for Bitcoin blockchain anchoring. Anchors are public at https://croviatrust.com/registry/data/substrate/ots_anchors.json.

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