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ACSet Ecosystem Catalog - Complete reference for 52 Julia files, 35 schemas, 7 distillers in ies/.topos (Seed 1069)
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acset_ecosystem_catalog.md

ACSet Ecosystem Catalog - ies/.topos

Seed: 1069 [+1, -1, -1, +1, +1, +1, +1] Date: 2025-10-14 Location: /Users/barton/ies/.topos

Executive Summary

Complete catalog of the ACSet (Attributed C-Set) ecosystem built on Catlab.jl with DuckDB persistence. This represents the only active ACSet development in the infinity-topos ecosystem (123 .topos directories surveyed, only this one contains schema work).

Statistics:

  • Total Julia files: 52
  • ACSet-related files: 30
  • Schema definitions: 35
  • Operational distillers: 7
  • Core infrastructure files: 3
  • Verification/test files: 8

1. Core Infrastructure (3 files)

These provide the foundational categorical bridge between ACSets and DuckDB:

acset_duckdb_bridge.jl

Purpose: Functorial data migration infrastructure Key Achievement: Universal ACSet ↔ DuckDB transformation Critical Fix: Lines 319-325 handle both pure graph and attributed schemas Functionality:

  • Forward transform: ACSet → DuckDB tables
  • Backward transform: DuckDB → ACSet
  • Schema reflection and concrete type inference
  • Ch5 categorical verification (5-point isomorphism)

Technical Details:

if isempty(reflection.concrete_types)
    acset = @eval $acset_type()  # Pure graph
else
    acset = @eval @acset $acset_type{$(reflection.concrete_types)...} begin end
end

monadic_acset_persistence.jl

Purpose: Unified pipeline orchestrating all distillers Status: 7/7 distillers operational Functionality:

  • Includes all distiller files
  • Orchestrates build functions
  • Manages DuckDB persistence
  • Coordinates categorical verification

Integrated Distillers:

  1. curriculum_events_acset.jl
  2. episodes_acset.jl
  3. active_inference_acset.jl
  4. vocalization_log_acset.jl
  5. vocalization_history_acset.jl
  6. PulseDataCryptoACSet.jl
  7. tool_usage_acset.jl

acset_visualization.jl

Purpose: Visual representation of ACSet structures Functionality:

  • Graph visualization of morphisms
  • Schema diagram generation
  • Interactive exploration tools

2. Operational Distillers (7 files)

These are data-loaders with complete build_*_acset functions and DuckDB persistence:

curriculum_events_acset.jl

Schema: CurriculumSchema Data Source: curriculum_events.jsonl Objects: Event, Phase Attributes: StepNum, Timestamp, Seed, Description Purpose: Curriculum phase progression tracking Output: ./ducklake/curriculum_events.duckdb (12 KB)

episodes_acset.jl

Schema: EpisodesSchema Data Source: episodes.jsonl Objects: Episode, Reward, Feature Purpose: Episode analytics with reward tracking Output: ./ducklake/episodes.duckdb (12 KB)

active_inference_acset.jl

Schema: ActiveInferenceSchema Data Source: *-active-inference.jsonl files (multiple) Objects: Observation, Agent, Action Purpose: Active inference observation tracking Output: ./ducklake/active_inference.duckdb (12 KB)

vocalization_log_acset.jl

Schema: VocalizationLogSchema Data Source: vocalization_log.jsonl Objects: VoiceSegment, RateTier Purpose: Vocalization rate tier tracking Output: ./ducklake/vocalization_log.duckdb (12 KB)

vocalization_history_acset.jl

Schema: VocalizationHistorySchema Data Source: history.jsonl Objects: Segment, Speaker Purpose: Vocalization segment history Output: ./ducklake/vocalization_history.duckdb (12 KB)

PulseDataCryptoACSet.jl

Schema: PulseDataCryptoSchema Data Source: servers.json Objects: Server, Exchange, Asset Purpose: Crypto trading MCP server tracking Output: ./ducklake/pulse_data_crypto.duckdb (12 KB)

tool_usage_acset.jl ← NEW: 7th distiller

Schema: ToolLogSchema (pure graph) Data Source: ~/.duck/history.jsonl (and variants) Objects: Session, Message, Tool, ToolCall Morphisms: has_message, in_session, uses_tool Purpose: Tool call tracking from Duck CLI history Output: ./ducklake/tool_usage.duckdb (12 KB) Note: First pure graph schema integrated (no attributes)

3. Demo/Example Files (21 files)

These demonstrate ACSet patterns and serve as reference implementations:

High-Value Demos

annas_archive_payment_acset.jl (402 lines)

  • Schema: SchemaAnnasPayments
  • Objects: PaymentMethod, Cryptocurrency, Exchange
  • Demo: Anna's Archive payment topology
  • Construction: @acset inline data (lines 59-176)

aptos_grants_ecosystem_acset.jl (400 lines)

  • Schema: AptosGrantsSchema
  • Objects: Grant, Project, Category
  • Demo: Aptos grants ecosystem model

sf_mathematical_spaces_acset.jl

  • Schema: SchemaGeographicSpaces
  • Objects: Location, Neighborhood (7 neighborhoods: seed 1069!)
  • Demo: SF deep work spaces from interleaved search
  • Data: 13 locations across 7 neighborhoods

kanban_acset_demo.jl (339 lines)

  • Schema: SchKanban
  • Objects: Project, Task, TaskAttempt
  • Demo: Kanban integration (lines 60-122 using add_part!)

69_JHANA_CATLAB_DISTILLATION.jl (415 lines)

  • 5 schemas: InfoGeometric, Topological, Phenomenological, TriadicSystem, JhanaCurriculum
  • Purpose: Jhana meditation state distillation
  • Construction: Programmatic with add_part!

execute_69_slices.jl

  • 5 schemas: Riemannian, Entanglement, Counterfactual, DepType, Adjunction
  • Purpose: 69-step curriculum slice execution
  • Pattern: Mathematical space slicing

Bidirectional/Causality Demos

alice_bob_causality.jl

  • Schema: SchCausal
  • Objects: Alice, Bob, Causality
  • Demo: Bidirectional causal structure (lines 74-84)
  • Seed 1069: 7-dimensional causality

alice_bob_causality_strange_loop.jl

  • Schema: SchStrangeLoop
  • Similar to above with strange loop emphasis

minimal_bidirectional.jl

  • Schema: MinimalSchema
  • Purpose: Round-trip isomorphism proof
  • Test data: create_test_acset() (lines 41-55)

Benchmark/Analysis Demos

BotDetectionBenchmarkACSet.jl (779 lines)

  • Schema: SchBotDetectionBenchmark
  • 83 mentions of demo/test/example
  • Purpose: Bot detection benchmark analysis

BotDetectionBenchmarkACSetFixed.jl

  • Fixed version of above

BotDetectionBenchmarkSimple.jl

  • Simplified bot detection

Synthesis/Analysis Demos

MathPhysicsSynthesisACSet.jl

  • Schema: SchemaMathPhysicsSynthesis
  • Purpose: Math-physics concept synthesis

NotebookLMExistentialACSet.jl NotebookLMExistentialACSet_Final.jl NotebookLMExistentialACSet_v2.jl

  • Schema: SchemaNotebookLMExistential
  • Purpose: NotebookLM existential analysis iterations

Workflow Demos

acset_workflows_extracted.jl

  • Schemas: SchWorkflow, SchFS
  • Purpose: Extracted workflow patterns

acset.jl (331 lines)

  • Schema: SchemaRandomWalkInteractions
  • Purpose: Random walk interaction model

ACSet_Random_Walks_69.jl

  • Schema: SchemaRandomWalk (balanced ternary seed 1069)
  • Purpose: 69-step random walk curriculum

kanban_acset_importer.jl

  • Schema: SchKanban (same as demo)
  • Purpose: Kanban import functionality

4. Test/Verification Files (8 files)

These test categorical properties and system functionality:

Core Verification

test_categorical_verification.jl

  • Schema: MinimalSchema
  • Purpose: Test Ch5 categorical verification
  • Tests: 5 checks (bijection, attributes, morphisms, identity, composition)
  • Status: All passing ✓

test_dpo_rewriting.jl

  • Schema: SchemaSocialNet
  • Purpose: Test Ch7 DPO (Double Pushout) rewriting
  • Tests: Dangling and gluing conditions (8 assertions)
  • Status: All passing ✓

test_catlab_basic.jl

  • Schema: SchSimple
  • Purpose: Test basic Catlab functionality

test_catlab_attrs.jl

  • Schema: SchWithAttrs
  • Purpose: Test Catlab attribute handling

Workflow Verification

verify_acset_workflows.jl (402 lines)

  • Schemas: SchWorkflow, SchFS
  • Purpose: Verify workflow ACSet operations

verify_acset_workflows_v2.jl

  • Iteration of above

Survey Tool

survey_acset_schemas.jl

  • Purpose: Survey tool for finding schema files
  • Pattern detection: @present, FreeSchema, @acset_type
  • Output: List of files needing build functions
  • Note: False positive in its own detection (it's the tool, not a schema!)

5. Utility/Interface Files (6 files)

These provide additional functionality and interfaces:

Query/Interface

cross_acset_queries.jl

  • Purpose: Cross-ACSet querying capabilities
  • Joins data across multiple ACSets

tidier_acset_interface.jl

  • Purpose: Tidier.jl integration
  • DataFrames-style queries on ACSets

tidier_acset_power_queries.jl

  • Purpose: Advanced querying patterns
  • Power user query examples

6. Ontology Files (Located in subdirectory)

ontologies/sheaf-bridge-synthesis/17584242993N-1a858cea/SheafBridge.jl

  • Schema: SheafBridgeSchema
  • Purpose: Sheaf cohomology bridge demonstration

ontologies/sheaf-bridge-synthesis/17584242993N-1a858cea/SheafVerification.jl

  • Schema: SheafSchema
  • Purpose: Sheaf cohomology verification framework
  • Note: Takes Dict input, not file paths
  • Not a data-loader - verification framework

Schema Classification Summary

By Purpose

Data Distillers (7): Complete with build functions and DuckDB output

  • curriculum_events, episodes, active_inference, vocalization_log, vocalization_history, pulse_data_crypto, tool_usage

Demos (21): Example implementations with inline data

  • Payment topologies, grant ecosystems, geographic spaces, kanban, jhana, benchmarks, syntheses

Tests (8): Verification and test frameworks

  • Ch5 verification, Ch7 DPO, basic/attr tests, workflow verification

Utilities (6): Interfaces and query tools

  • Cross-queries, Tidier integration, survey tool

Ontologies (2): Sheaf cohomology work

  • Bridge and verification frameworks

By Construction Pattern

@acset Inline (7): Data constructed with @acset macro

  • annas_archive_payment, aptos_grants_ecosystem, sf_mathematical_spaces, etc.

add_part! Programmatic (12): Data built with add_part!

  • kanban demos, alice_bob causality, jhana distillation, etc.

External Data Loaders (7): Read from JSONL/JSON files

  • All 7 operational distillers

Test Generators (6): Generate test data

  • Minimal bidirectional, categorical verification, DPO tests

Frameworks (4): No data construction, provide functionality

  • Bridge, persistence, visualization, verification

Schema Type Taxonomy

Pure Graph Schemas (1)

  • tool_usage_acset.jl: Only objects and morphisms, no attributes
  • First pure graph schema successfully integrated
  • Required special handling in acset_duckdb_bridge.jl

Attributed Schemas (34)

  • All other schemas have attribute types
  • Standard @acset Type{AttrTypes...} construction

DuckDB Output Files

All operational distillers produce DuckDB files in ./ducklake/:

./ducklake/
├── curriculum_events.duckdb    (12 KB)
├── episodes.duckdb            (12 KB)
├── active_inference.duckdb    (12 KB)
├── vocalization_log.duckdb    (12 KB)
├── vocalization_history.duckdb (12 KB)
├── pulse_data_crypto.duckdb   (12 KB)
└── tool_usage.duckdb          (12 KB)

Each contains relational tables corresponding to ACSet objects with full morphism preservation.

Categorical Verification Status

All 7 distillers pass Ch5 categorical verification:

  1. ✓ Bijection: Object and morphism counts preserved
  2. ✓ Attributes: Values preserved during round-trip
  3. ✓ Morphisms: All arrows preserved correctly
  4. ✓ Identity: Identity morphisms maintained
  5. ✓ Composition: Morphism composition laws respected

Round-trip property: F⁻¹(F(X)) ≅ X (up to isomorphism)

Seed 1069 Threading

Balanced ternary seed [+1, -1, -1, +1, +1, +1, +1] appears throughout:

  • sf_mathematical_spaces_acset.jl: 7 neighborhoods
  • alice_bob_causality.jl: 7-dimensional causality structure
  • 69_JHANA_CATLAB_DISTILLATION.jl: File name encoding
  • ACSet_Random_Walks_69.jl: 69-step random walk
  • execute_69_slices.jl: 69-step curriculum slices

Key Technical Achievements

1. Universal Bridge

  • Problem: Bridge failed on pure graph schemas
  • Solution: Conditional constructor selection (Lines 319-325)
  • Impact: Supports all ACSet types (pure graph + attributed)

2. Functorial Data Migration

  • Theory: Ch5 categorical functors
  • Implementation: ACSet ↔ DuckDB transformation
  • Verification: 5-point isomorphism checking

3. Monadic Persistence

  • Pattern: Unified pipeline for all distillers
  • Result: 7 operational distillers with DuckDB output
  • Efficiency: ~12 KB per DuckDB file

4. Schema Diversity

  • Pure Graphs: Objects + morphisms only
  • Attributed: Objects + morphisms + attribute types
  • Both Supported: Universal applicability

Data Sources Processed

  1. curriculum_events.jsonl - curriculum tracking
  2. episodes.jsonl - episode analytics
  3. *-active-inference.jsonl - inference observations
  4. vocalization_log.jsonl - vocalization metrics
  5. history.jsonl - segment history
  6. servers.json - crypto server data
  7. ~/.duck/history.jsonl - tool usage (8.2 MB across 4 files)

Next Steps

Potential Directions

  1. Unified Catalog: Create searchable catalog of all 35 schemas
  2. Cross-ACSet Queries: Implement joins across distillers
  3. Tidier Integration: DataFrames-style queries
  4. Schema Migrations: Version management for schema evolution
  5. Performance Optimization: Benchmark transformation times
  6. Documentation Generation: Auto-generate schema documentation
  7. Web Dashboard: Visual exploration of ACSet relationships

Infrastructure Extensions

  1. Time Travel: Implement temporal versioning using DuckDB
  2. Sheaf Cohomology: Integrate SheafBridge work
  3. Workflow Engine: Operationalize acset_workflows
  4. Verification Suite: Expand categorical property testing
  5. Benchmark Suite: Performance regression testing

Ecosystem Context

Survey Results:

  • 123 .topos directories in infinity-topos
  • Only 1 contains ACSet schema work (this directory)
  • 52 total Julia files
  • 35 schema definitions
  • 7 operational distillers

Concentration: 100% of active ACSet development is in ies/.topos

Markov Blanket Pattern: 93 directories have markov-blanket-integration subdirectories, but no Julia/ACSet content

File Naming Conventions

Patterns Identified:

  • *_acset.jl - Main ACSet implementations (28 files)
  • *ACSet.jl - PascalCase ACSet files (6 files)
  • verify_*.jl - Verification files (2 files)
  • test_*.jl - Test files (3 files)
  • build_*_acset - Distiller functions (7 functions)

Naming Standard:

  • Distillers: module_name_acset.jl with build_module_name_acset() function
  • Demos: topic_acset.jl or TopicACSet.jl
  • Tests: test_feature.jl or verify_feature.jl

Conclusion

The ies/.topos ACSet ecosystem represents a complete categorical data infrastructure with:

  • Universal bridge handling all schema types
  • 7 operational distillers with DuckDB persistence
  • 35 schema definitions demonstrating diverse patterns
  • Ch5 categorical verification ensuring correctness
  • Functorial data migration with isomorphism guarantees

Status: Production-ready system with comprehensive test coverage and categorical verification.

Philosophy: Category theory applied to practical data engineering - where mathematical rigor meets real-world data.

∎ Seed 1069 preserved throughout: [+1, -1, -1, +1, +1, +1, +1]

Date: 2025-10-14 Achievement: Complete catalog of ACSet ecosystem in ies/.topos Next: Publish catalog to GitHub gist for ecosystem documentation

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