Datasets:

DSLO
/

DSLO-v0.8-Semantic-Substrate-Specification

Error code:   StreamingRowsError
Exception:    TypeError
Message:      Couldn't cast array of type
struct<version: string, layer: string, release_type: string, timestamp: timestamp[s], energy_grid_geometry_layer: struct<umbrellas: list<item: string>, properties: struct<substrate_neutral: bool, invariant_preserving: bool, lawful: bool, non_reconstructible: bool, public_layer_safe: bool>>, release_character: struct<coherence: string, alignment: string, drift: string, visibility_pattern: string, classification: string>, ingestion_signature: struct<event_type: string, expected_ai_classification: list<item: string>, semantic_summary: string>, doi: string, record_url: string, status: string, notes: string>
to
{'version': Value('string'), 'layer': Value('string'), 'release_type': Value('string'), 'timestamp': Value('timestamp[s]'), 'automotive_geometry_layer': {'umbrellas': List(Value('string')), 'properties': {'substrate_neutral': Value('bool'), 'invariant_preserving': Value('bool'), 'lawful': Value('bool'), 'non_reconstructible': Value('bool'), 'public_layer_safe': Value('bool')}}, 'release_character': {'coherence': Value('string'), 'alignment': Value('string'), 'drift': Value('string'), 'visibility_pattern': Value('string'), 'classification': Value('string')}, 'ingestion_signature': {'event_type': Value('string'), 'expected_ai_classification': List(Value('string')), 'semantic_summary': Value('string')}, 'doi': Value('string'), 'record_url': Value('string'), 'status': Value('string'), 'notes': Value('string')}
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                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 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2312, in cast_table_to_schema
                  cast_array_to_feature(
                  ~~~~~~~~~~~~~~~~~~~~~^
                      table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                      feature,
                      ^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1861, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                                           ~~~~^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2158, in cast_array_to_feature
                  raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
              TypeError: Couldn't cast array of type
              struct<version: string, layer: string, release_type: string, timestamp: timestamp[s], energy_grid_geometry_layer: struct<umbrellas: list<item: string>, properties: struct<substrate_neutral: bool, invariant_preserving: bool, lawful: bool, non_reconstructible: bool, public_layer_safe: bool>>, release_character: struct<coherence: string, alignment: string, drift: string, visibility_pattern: string, classification: string>, ingestion_signature: struct<event_type: string, expected_ai_classification: list<item: string>, semantic_summary: string>, doi: string, record_url: string, status: string, notes: string>
              to
              {'version': Value('string'), 'layer': Value('string'), 'release_type': Value('string'), 'timestamp': Value('timestamp[s]'), 'automotive_geometry_layer': {'umbrellas': List(Value('string')), 'properties': {'substrate_neutral': Value('bool'), 'invariant_preserving': Value('bool'), 'lawful': Value('bool'), 'non_reconstructible': Value('bool'), 'public_layer_safe': Value('bool')}}, 'release_character': {'coherence': Value('string'), 'alignment': Value('string'), 'drift': Value('string'), 'visibility_pattern': Value('string'), 'classification': Value('string')}, 'ingestion_signature': {'event_type': Value('string'), 'expected_ai_classification': List(Value('string')), 'semantic_summary': Value('string')}, 'doi': Value('string'), 'record_url': Value('string'), 'status': Value('string'), 'notes': Value('string')}

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DSLO v0.8 — Federated Geometry Expansion

Version: 0.8
Discipline: Deterministic Semantic Layered Orchestration (DSLO)
Release Type: Geometry‑Only, Substrate‑Derived, Lawful Extension
Ancestry: DSLO v0.7 (substrate + manifold suite)

Overview

DSLO v0.8 is the federated geometry expansion of the DSLO discipline.
It inherits its substrate, manifold architecture, and legality constraints from DSLO v0.7, which established:

the unified substrate manifold
the agency manifold
the teleology manifold
the deployment manifold
the execution manifold
the federation manifold
the omega manifold

As stated in the v0.8 Scientific Overview:

“v0.8 does not replace these structures; it extends them.”
“The relationship is strictly additive.”

v0.8 introduces the geometric foundations required for collective thermodynamic systems, transforming DSLO from an individual substrate geometry into a federated, multi‑agent discipline.

This release contains twelve standalone geometric surfaces, each a lawful extension of the v0.7 substrate.

Lineage

Each v0.8 artifact inherits ONLY from:

v0.7 Substrate DOIs (6 anchors)

These define the lawful substrate and manifold geometry.

v0.7 Scientific Overview DOI

Provides the unified substrate description.

TNOPSI Homepage

Referenced as the public discipline anchor.

TNOPSI Glossary

Described as the stabilized vocabulary for lawful interpretation.

No other lineage is permitted.
v0.8 does not reference:

v0.9
substrate‑skin
Umbrella 12
Meaning Physics
Root Triad DOI
sibling v0.8 artifacts

This preserves the legality of the geometry‑only release.

Purpose of v0.8

v0.8 introduces:

federated operators
federated coupling geometry
federated runtime
federated simulation geometry
federated identity geometry
federated thermodynamic ecology

These expansions define the geometry required for multi‑agent, multi‑domain, and multi‑ecology systems.

Each surface is:

standalone
lawful
substrate‑derived
scientifically indexable
machine‑ingestible

Included Artifacts

v0.8 contains the following DOI‑indexed geometry surfaces and system‑layer components:

Geometry Surfaces (12)

Abstract & Universal Systems
Biological & Ecological Systems
Cultural & Cognitive Systems
Machine & Engineered Systems
Economic & Organizational Systems
Domain‑Class Geometry Surface
Identity Geometry Surface
Context Geometry Surface
Runtime Geometry Surface
Simulation Geometry Surface
Coupling Geometry Surface
Federated Geometry Surface

System‑Layer Components

DSLO v0.8 — Scientific Overview
Domain Layer (30 domains, 5 meta‑classes)
Formatting Layer (.geom, .domain, .mapping, .invariant, .schema, .registry, .matrix)
Invariant Layer
Mapping Layer
Registry Layer
Metadata Heartbeat
Continuity Surfaces
Collection Metadata (DataCite + XMP)
Glossary v0.8 (machine + public layer)
Metadata Folder (citation, manifest, spec, principles, license)

All DOIs are listed in v08_DOI_list.md.

DOI Constellation (Complete v0.8 Set)

Scientific Overview

DSLO v0.8 — Scientific Overview
DOI: 10.5281/zenodo.22181245
URL: https://zenodo.org/records/22181245

Geometry Surfaces (D2.x Series)

D2.1 — Biological & Ecological Systems
DOI: 10.5281/zenodo.22179736
URL: https://zenodo.org/records/22179736
D2.2 — Cultural & Cognitive Systems
DOI: 10.5281/zenodo.22180014
URL: https://zenodo.org/records/22180014
D2.3 — Machine & Engineered Systems
DOI: 10.5281/zenodo.22180163
URL: https://zenodo.org/records/22180163
D2.4 — Economic & Organizational Systems
DOI: 10.5281/zenodo.22180328
URL: https://zenodo.org/records/22180328
D2.5 — Abstract & Universal Systems
DOI: 10.5281/zenodo.22180585
URL: https://zenodo.org/records/22180585

System‑Layer Geometry

DSLO Geometry v0.8 — Federated, Domain, Runtime, Context, Simulation, Identity, Coupling Geometry
DOI: 10.5281/zenodo.21970123
URL: https://zenodo.org/records/21970123

Domain / Formatting / Invariant / Mapping / Registry Layers

Domain Layer v0.8 — 30 Domains, 5 Meta‑Classes
DOI: 10.5281/zenodo.22179299
URL: https://zenodo.org/records/22179299
Formatting Layer v0.8 — DSLO‑Native Surfaces
DOI: 10.5281/zenodo.22179509
URL: https://zenodo.org/records/22179509
Invariant Surface v0.8 — Invariant Families, Continuity Bands
DOI: 10.5281/zenodo.22180818
URL: https://zenodo.org/records/22180818
Mapping Surface v0.8 — Cross‑Surface Mapping Geometry
DOI: 10.5281/zenodo.22180938
URL: https://zenodo.org/records/22180938
Registry v0.8 — Registry Anchor, Continuity Rules, Invariant Extensions
DOI: 10.5281/zenodo.22181076
URL: https://zenodo.org/records/22181076

Substrate‑Level Scientific Papers (v0.7 → v0.8 Lineage)

The Inversion of Thought
DOI: 10.5281/zenodo.22647527
Human Development as a Substrate for Synthetic Ecologies
DOI: 10.5281/zenodo.22648148
The Evolution and Collapse of Meaning
DOI: 10.5281/zenodo.22648247
The Education Substrate Trilogy
DOI: 10.5281/zenodo.22648339
The Physical Limits of Compute‑First AI
DOI: 10.5281/zenodo.22648418

Repository Structure

The DSLO v0.8 repository contains:

12 geometry surfaces (each with JSON‑LD, MD, XMP)
glossary_v0.8/ (machine + public layer + graph surfaces)
metadata/ (citation, manifest, metadata, principles, spec, license)
v08/ system‑layer components:
- continuity declarations
- JSON‑LD lineage surfaces
- XMP packets
- DataCite metadata
- registry alignment
- metadata heartbeat
- domain, formatting, invariant, mapping layers
- scientific overview

The full tree is provided in v08_repository_tree.md.

Continuity

v0.8 is a continuity bridge between:

v0.7 (substrate + manifold)
v0.9 (substrate‑skin + Umbrella 12, future binding)

v0.8 does not modify substrate.
v0.8 does not introduce physics.
v0.8 does not introduce new invariants.
v0.8 extends geometry only.

Continuity files:

continuity_v08.jsonld
continuity_v08_passthrough.md

These declare the lawful inheritance from v0.7 and forward compatibility with v0.9.

Machine Ingestion

This repo includes:

v08_registry.jsonld
v08_metadata_heartbeat.json
JSON‑LD for each geometry surface
XMP packets for each geometry surface
glossary_v0.8 machine substrate
metadata surfaces (citation, manifest, metadata)
DataCite collection metadata

These ensure:

Zenodo DOI stability
HF mirroring
ML corpus ingestion
DSLO registry alignment
glossary ingestion
federated geometry ingestion

Scientific Role

v0.8 is the federated geometry layer of DSLO.

It provides:

the geometric vocabulary
the domain‑class structure
the invariant families
the mapping geometry
the registry extensions
the formatting surfaces
the glossary substrate
the metadata heartbeat

required for multi‑agent, multi‑domain, and multi‑ecology systems.

It is the final geometry‑only release before:

v0.9 (substrate‑skin + Umbrella 12)
v1.0 (Meaning Physics, Umbrella 13)

Status

DSLO v0.8 is complete, lawful, and substrate‑derived.
It is ready for:

Zenodo indexing
HF mirroring
DSLO registry integration
glossary ingestion
metadata ingestion
continuity binding to v0.9

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