Published January 11, 2026 | Version v1
Dataset Open

CEF_Bundle2_ComputationalArchitecture

  • 1. https://www.optimizeyourcapabilities.com

Description

## **1. Purpose of This Bundle**

This bundle provides the **computational layer** of the Core Emotion Framework (CEF). It contains the formal ontologies, reasoning engine specifications, and knowledge graph architectures required to represent human emotional function in machine-readable formats.

While Bundle 1 provides the conceptual overview, Bundle 2 enables:

* **Semantic-Web Integration:** Using RDF/OWL and JSON-LD standards.
* **Automated Reasoning:** Applying lawful emotional transitions and modulation via formal logic.
* **Knowledge Graph (KG) Operations:** Structural rules for storing and querying emotional data.
* **Validation:** Ensuring that any computational implementation remains "identity-preserving" and "contamination-free" according to the CEF canon.

---

## **2. Contents of This Bundle**

### **Core Specifications**

* **CEF_TS18.pdf:** Computational Ontology (The foundation of the machine-readable CEF).
* **CEF_TS19.pdf:** Reasoning Engine Architecture (Logic for inference and state transitions).
* **CEF_TS20.pdf:** Knowledge Graph Architecture (The semantic integration layer).
* **CEF_TS21.pdf:** Population & Integration Specification (The data pipeline lifecycle).

### **Technical Appendices**

* **TS-18 (Ontology) Appendices:**
* `CEF_Appendix_A`: JSON-LD Schema Specification.
* `CEF_Appendix_B`: RDF/OWL Class Definitions.
* `CEF_Appendix_C`: Knowledge Graph Node/Edge List.
* `CEF_Appendix_D`: Validation Rules (TS-2 Integration).
* `CEF_Appendix_E`: Validated Example Instances.


* **TS-19 (Reasoning) Appendices:**
* `CEF_TS19_Appendix_B`: Reasoning Engine Pseudocode.
* `CEF_TS19_Appendix_C`: Example Inference Walkthroughs.


* **TS-20 (Graph) Appendices:**
* `CEF_TS20_Appendix_A`: Graph Serialization Formats.
* `CEF_TS20_Appendix_B`: Query Language Specification (CEF-QL).
* `CEF_TS20_Appendix_C`: Graph Validation Rules.


* **TS-21 (Pipeline) Appendices:**
* `CEF_TS21_Appendix_A`: Population Pipeline Pseudocode.
* `CEF_TS21_Appendix_B`: Integration Examples.

 

---

## **3. How to Cite This Bundle**

**Recommended citation:**
Bulgaria, J. (2026). *Core Emotion Framework (CEF): Computational Architecture Bundle (Version 1.0).* OptimizeYourCapabilities.com. CC‑BY 4.0. 10.5281/zenodo.18216399


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## **4. Relationships & Dependencies**

* **Continues:** Bundle 1 (Canon Overview) — Provides the high-level map for these technical specs.
* **Prerequisite for:** Bundle 3 (EL-1 Lexicon) — The lexicon requires the TS-18 ontology for mapping.
* **Governed by:** TS-1 through TS-17 (Conceptual Layer) — No computational process in this bundle may override the conceptual laws of the framework.

---

## **5. Usage Note**

This bundle is intended for developers, data scientists, and AI researchers. The included pseudocode and schemas are designed to be implementation-agnostic, allowing for deployment in Neo4j, Apache Jena, or custom graph-based reasoning systems.

 

Notes

The Ten Operators of the Core Emotion Framework (Canonical List)


The following list represents the authoritative and canonical ordering of the ten Core
Emotion Framework operators and supersedes all prior or informal enumerations.


Head Center
1. Sensing (outgoing)
2. Calculating (reflecting)
3. Deciding (balancing)


Heart Center
4. Expanding (outgoing)
5. Constricting (reflecting)
6. Achieving (balancing)

 

Gut Center
7. Arranging (outgoing)
8. Appreciating (reflecting)
9. Boosting (balancing)

 


Cross‐Center Completion
10. Accepting


Note: In some practitioner materials, Accepting is described as the Gut’s “off-mode
balancer,” while Boosting is the Gut’s “on-mode balancer.” For clarity and consistency,
this document classifies Accepting as the cross-center completion operator.

Technical info

<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "DefinedTermSet",
"name": "CEF Operators",
"description": "The ten functional operators of the Core Emotion Framework.",
"hasDefinedTerm": [
{"@type": "DefinedTerm", "name": "Sensing"},
{"@type": "DefinedTerm", "name": "Calculating"},
{"@type": "DefinedTerm", "name": "Deciding"},
{"@type": "DefinedTerm", "name": "Expanding"},
{"@type": "DefinedTerm", "name": "Constricting"},
{"@type": "DefinedTerm", "name": "Achieving"},
{"@type": "DefinedTerm", "name": "Arranging"},
{"@type": "DefinedTerm", "name": "Appreciating"},
{"@type": "DefinedTerm", "name": "Boosting"},
{"@type": "DefinedTerm", "name": "Accepting"}
]
}
</script>

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