MCog Core: A Metacognition Ontology

MCog Core v2.1 – Biomimicry & Ephemeral Cognition
A domain-agnostic ontology capturing advanced metacognitive constructs, refined and expanded to mirror nature’s adaptive processes in cognitive reasoning.

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Table of Contents

• Overview
• Key Features
• What's New in v2.1
• Ontology Specification
• Example Usage
• Design Principles
• Installation
• Usage
• Configuration
• Testing
• Future Directions
• Contributing
• License
• Citation
• Contact
• Acknowledgements

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Overview

MCog Core is a domain-agnostic ontology designed to represent fundamental metacognitive constructs for AI systems, cognitive architectures, decision support tools, and educational applications. Now in its v2.1 release, the ontology has evolved from its earlier quantum/stealth-focused design (v2.0) toward a richer, biomimicry-inspired framework that embraces natural, ephemeral cognitive processes—mirroring the fleeting and adaptive nature of biological thought.

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Key Features

• Domain Agnostic & Modular:
  Designed for reuse and extension across diverse projects.

• Advanced Metacognitive Modeling:
  Captures reasoning processes, heuristics, hypotheses, reflections, biases, and confidence assessments.

• Ephemeral Cognition & Biomimicry:
  New classes such as EphemeralCognitionProcess and BiomimeticDimension model fleeting cognitive states and nature-inspired adaptive feedback loops.

• Backward Compatibility:
  Retains all constructs from previous versions while adding new functionalities.

• Open Source & Iteratively Developed:
  Continuously refined based on research insights and community feedback.

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What's New in v2.1

This release introduces a refined approach to representing ephemeral states and biomimetic processes:

1. EphemeralCognitionProcess:

   • Models transient mental states akin to fleeting thoughts.
   • Introduces the transientLevel property to quantify fleetingness.

2. BiomimeticDimension:

   • A subclass of Reflection capturing nature-inspired adaptive cycles.
   • Provides a metaphor for iterative reflections similar to natural processes.

3. Enhanced Relationships:

   • New object property hasEphemeralFocus links fleeting cognition instances to their temporary reflections.

4. Updated “Stealth Modality” Description:

   • Reframes stealth features to align with transient and unarticulated aspects of cognitive reasoning.

5. Version Bump:

   • The ontology is now marked as v2.1—signifying a major evolutionary step in its conceptual design.

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Ontology Specification

The MCog Core ontology is provided in Turtle format. Below is an excerpt showcasing new and updated sections of the ontology:

@prefix mcog-core: <https://github.com/galaxy-brain-ai/mcog-core#> .
@prefix dct: <http://purl.org/dc/terms/> .
@prefix owl: <http://www.w3.org/2002/07/owl#> .
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .

################################################################################
# NEW BIOMIMICRY & EPHEMERAL CLASSES (V2.1)
################################################################################

mcog-core:EphemeralCognitionProcess a owl:Class ;
  rdfs:label "Ephemeral Cognition Process" ;
  rdfs:subClassOf mcog-core:ReasoningProcess ;
  dct:description """
A short-lived or transient reasoning process, analogous to fleeting thoughts in 
biological cognition. Ephemeral cognitions might never reach full articulation 
unless captured or reflected upon in time.
"""@en .

mcog-core:BiomimeticDimension a owl:Class ;
  rdfs:label "Biomimetic Dimension" ;
  rdfs:subClassOf mcog-core:Reflection ;
  dct:description """
A reflection approach or layer that emulates cycles observed in natural systems—iterative 
adaptation, emergence, and dissolution. Captures how ephemeral or stealth-like states 
arise, transform, or vanish similarly to adaptive processes in living organisms.
"""@en .

################################################################################
# NEW OBJECT PROPERTY: hasEphemeralFocus
################################################################################

mcog-core:hasEphemeralFocus a owl:ObjectProperty ;
  rdfs:label "has Ephemeral Focus" ;
  rdfs:domain mcog-core:EphemeralCognitionProcess ;
  rdfs:range mcog-core:Reflection ;
  dct:description "Indicates a reflection (or set of reflections) that momentarily captured or addressed an otherwise fleeting cognition process."@en .

################################################################################
# NEW DATATYPE PROPERTY: transientLevel
################################################################################

mcog-core:transientLevel a owl:DatatypeProperty ;
  rdfs:label "transient Level" ;
  rdfs:domain mcog-core:EphemeralCognitionProcess ;
  rdfs:range xsd:float ;
  dct:description "A measure (0.0 to 1.0) indicating how fleeting or short-lived an ephemeral cognition process is. Higher values suggest more rapid dissipation."@en .

A complete Turtle file is provided for full reference.

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Example Usage

Below is an example demonstrating how to create an instance of an ephemeral cognition process and link it to a biomimetic reflection:

@prefix mcog-core: <https://github.com/galaxy-brain-ai/mcog-core#> .
@prefix ex: <http://example.org/resource/> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .

# Define an ephemeral cognition instance with a high transient level
ex:fleeting-idea-001 a mcog-core:EphemeralCognitionProcess ;
  mcog-core:transientLevel "0.85"^^xsd:float ;
  mcog-core:usesHeuristic ex:heuristic-fuzzy-imagery .

ex:heuristic-fuzzy-imagery a mcog-core:Heuristic ;
  mcog-core:heuristicName "Fuzzy, imagery-based mental shortcut"@en .

# Define a biomimetic reflection capturing the fleeting idea
ex:brief-reflection-001 a mcog-core:BiomimeticDimension ;
  mcog-core:reflectionTimestamp "2025-01-19T10:00:00Z"^^xsd:dateTime ;
  mcog-core:reflectionText "A short-lived intuitive flash about an approach to solve problem X, reminiscent of ephemeral patterns in nature."@en ;
  mcog-core:reflectsOn ex:fleeting-idea-001 .

# Link the ephemeral cognition to the reflection
ex:fleeting-idea-001 mcog-core:hasEphemeralFocus ex:brief-reflection-001 .

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Design Principles

• Clarity & Flexibility:
  Every class and property is clearly defined using descriptive annotations, ensuring broad applicability without over-restrictive constraints.

• Iterative & Adaptive Development:
  MCog Core is continually enhanced by incorporating real-world insights from research (including our latest biomimicry-inspired extensions).

• Backward Compatibility:
  Updates and new features (v2.1) maintain all existing classes and relationships from earlier versions.

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Installation

1. Clone the Repository:

   git clone https://github.com/galaxy-brain-ai/mcog-core.git
   cd mcog-core

2. Download the Ontology File:

   The main ontology file is available in Turtle format as mcog-core.ttl.

3. Integrate into Your Project:

   Import the ontology file into your semantic framework or RDF-aware system as required.

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Usage

To integrate MCog Core into your application:

• For RDF-based reasoning:
  Load mcog-core.ttl into your RDF store or triple store.

• For programmatic access:
  Use your favorite ontology parser (e.g., Apache Jena for Java, RDFlib for Python) to access and traverse the metacognitive constructs.

• For research and demonstration purposes:
  Utilize provided examples to model reasoning processes, capture ephemeral cognitions, and record adaptive reflections.

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Configuration

• Customization:
  Modify or extend classes and properties as necessary to suit your domain-specific needs.

• Namespaces:
  Ensure your tools recognize the namespace https://github.com/galaxy-brain-ai/mcog-core# for proper linking of ontology components.

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Testing

For automated testing of your ontology:

1. Validate the Turtle File:
   Use ontology validation tools like the W3C RDF Validator or OntoGraf.

2. Run SPARQL Queries:
   Test specific reasoning cases using SPARQL queries to ensure expected inferences and mappings.

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Future Directions

Planned enhancements include:

• Bias Taxonomy Expansion:
  Develop a detailed hierarchical representation of cognitive biases.

• Enhanced Heuristic Modeling:
  Provide more granular definitions and examples for diverse heuristic approaches.

• Integration with Cognitive Architectures:
  Explore integration pathways with existing cognitive and neural network models.

• Additional Reflective Layers:
  Further refine the relationship between fleeting, subconscious states and fully articulated reflections.

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Contributing

All additions welcome! If you have ideas, improvements, or find issues:

• Issues & Pull Requests:
  Please open issues or submit pull requests via the SOURCE GitHub repository.

• Guidelines:
  We welcome contributions to MCog Core! If you have suggestions for improvements or extensions, please open an issue or submit a pull request on this repository.

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License

MCog Core is distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

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Citation

If you use MCog Core in your research or applications, please cite the project as follows:

Shep Bryan, Galaxy Brain AI. (2025). MCog Core: A Metacognition Ontology (Version 2.1 – Biomimicry & Ephemeral Cognition) [Ontology Resource]. Retrieved from https://github.com/galaxy-brain-ai/mcog-core.

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Contact

For questions, feedback, or further collaboration:

David Youngblood
@TheDavidYoungblood
LinkedIn • Medium • Twitter/X

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Acknowledgements

• Special thanks to the original MCog Core authors and community contributors.
• Research enhancements provided by David Youngblood at LouminAI Labs, whose interdisciplinary insights continue to drive the evolution of this ontology.
• Gratitude to all those in the open-source and academic communities for their invaluable feedback.

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Empowering cognitive modeling one fleeting thought at a time—join us on the journey toward a more reflective and adaptive digital age!