The Is: An Ontological Framework v2.0 — Formal System Proposal
This release presents The Is Framework v2.0, a formal ontological system grounded in five irreducible axioms (T1–T5), derived theorems, a proposed ontological partial order, invariance principles, and a structured falsifiability architecture (C1–C11). Building on v1.0–v1.3, which established the conceptual foundation, systematic architecture, operational precision, and cross-framework case studies, v2.0 introduces a formal system proposal centered on the generative ontological sequence: The Is (I) → Difference (D) → Structure (S) → Appearance (A) → Feedback (F) From this sequence, the framework develops: Axiomatic Foundation (T1–T5) Ontological Dependency Graph Proposed Ontological Partial Order The Is Invariance Principle Derived Theorems (C2–C4) Formal Correspondence Architecture Cross-Framework Integration Falsifiability Architecture (C1–C11) Roadmap toward Formal Mapping (v2.1) and Meta-Ontology (v3.0) The framework further formalizes illustrative correspondences to three existing research programs: Structural Differentiation Cosmology (SDC) Topological Latent Manifold Model (TLMM) Appearance-Based Framework (ABF) These correspondences are explicitly interpretive rather than identity mappings and are intended to demonstrate the framework's domain-agnostic ontological scope. All figures, mappings, axioms, theorems, and falsifiability criteria are conceptual and methodological. The framework is presented as a formal ontological proposal and should not be interpreted as a physical, clinical, or behavioral equivalence model. This release includes: Full manuscript (PDF) Figure set (Fig.1–Fig.16) Demo figure-generation script (the_is_framework_v20_demo.py) Documentation (README.md) The long-term objective of the framework is the development of a formal meta-ontological architecture capable of organizing and interpreting multiple domain-specific theoretical systems through a shared ontological structure.
Authors
- Koji Okino (ORCID: https://orcid.org/0009-0003-9273-9813)
Institutions
- United States Department of Labor (US)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-06-08
- DOI
- https://doi.org/10.5281/zenodo.20593523
- Primary Topic
- Biomedical Text Mining and Ontologies
- Type
- preprint