MLKN.lab · Polyhierarchy

Polyhierarchy

6 Core Domains → 25 Disciplines → 235 Subdisciplines → Topics & Concepts

Overview Knowledge Layers Core Domains Academic Disciplines Visualization Exploration

Overview

A Polyhierarchical and Mutli-Layered Knowledge Network

Overview Knowledge Layers Core Domains Academic Disciplines Visualization Exploration

The structural architecture of MLKN.lab is anchored in a formalized, five-tier ontological taxonomy designed to map the multi-scale density of global science. Moving past the cognitive limitations of linear, mono-hierarchical indexing, this taxonomy employs a high-fidelity, polyhierarchical framework that allows complex scientific entities and boundary concepts to map concurrently across multiple fluid conceptual pathways.

The structural schema is partitioned into five discrete abstraction layers (5 Ontological Knowledge Layers): expanding from Layer 1 (6 Epistemological Core Domains) which establish macro-disciplinary baselines, down through Layer 2 (25 Academic Disciplines) and Layer 3 (235 Specialized Subfields), into the granular clusters of Layer 4 (Thematic Domains) and Layer 5 (Core Concepts). This stratified taxonomy acts as the structural blueprint for our knowledge graphs, providing the mathematical and conceptual scaffolding necessary to trace cross-domain knowledge diffusion, measure cluster modularity, and systematically isolate under-explored interdisciplinary frontiers.

Knowledge Layers Core Domains Academic Disciplines Subdisciplines Topics Concepts

Polyhierarchical Multi-layered Nodes Edges

Conceptual Foundations

Multilayer Networks & Hypergraphs in MLKN.lab

Overview Conceptual Foundations Knowledge Layers Core Domains Academic Disciplines Visualization Exploration

MLKN.lab's polyhierarchical framework is built on two complementary mathematical structures: multilayer networks (Layers 1-4) and hypergraphs (Layers 4-5). This dual approach allows us to model both hierarchical relationships (e.g., disciplines containing subdisciplines) and complex, non-linear connections (e.g., concepts spanning multiple fields).

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Multilayer Network (Layers 1-4)

Layers 1-4 form a hierarchical network where:

Layer 1 (Core Domains): 6 broad categories (e.g., Natural Sciences)
Layer 2 (Disciplines): 25 fields (e.g., Physics)
Layer 3 (Subdisciplines): 235 specialized areas (e.g., Quantum Mechanics)
Layer 4 (Thematic Domains): Granular clusters (e.g., Quantum Field Theory)

This structure enables top-down analysis of knowledge diffusion across traditional academic boundaries.

Hierarchical Tree-like Parent-Child

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Hypergraph (Layers 4-5)

Layers 4-5 form a hypergraph where:

Layer 4 (Thematic Domains): Connects to multiple disciplines
Layer 5 (Concepts): Links to multiple thematic domains

This allows non-linear mapping of concepts that span multiple fields (e.g., "Machine Learning" in CS, Math, and Neuroscience).

Non-Linear Multi-Edge Cross-Domain

Combined Framework

The multilayer network (Layers 1-4) and hypergraph (Layers 4-5) work together to:

Preserve disciplinary hierarchy (e.g., Physics → Quantum Mechanics)
Enable cross-disciplinary connections (e.g., Quantum Mechanics → Chemistry)
Support multi-scale analysis (from domains to concepts)

Polyhierarchical Multi-Scale Interdisciplinary

OpenAlex Integration

Our implementation uses OpenAlex data to:

Map 25 disciplines to 6 core domains
Identify 235 subdisciplines with cross-domain connections
Track 320K+ connections between concepts

This creates a data-driven polyhierarchy that reflects real-world scientific relationships.

Explore OpenAlex

For a rigorous mathematical treatment of these concepts, see our MLKN.model - Mathematical Foundations page.

Ontological Knowledge Layers

5 Knowledge Layers

Overview Knowledge Layers Core Domains Academic Disciplines Visualization Exploration

The MLKN.lab polyhierarchy organizes scientific knowledge into 5 layers:

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Core Domains

Layer 1: 6 broad categories (e.g., Social Sciences & Humanities, Natural Sciences).

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Academic Disciplines

Layer 2: 25 fields (e.g., Psychology, Computer Science).

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Subdisciplines

Layer 3: 235 specialized areas (e.g., Cognitive Psychology, AI Ethics).

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Core Thematic Domains

Layer 4: Thematic groupings within subdisciplines.

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Main Concepts

Layer 5: Specific topics or ideas (e.g., "Attention", "Neural Networks").

Epistemological Core Domains

6 High-Level Scientific Domains

Overview Knowledge Layers Core Domains Academic Disciplines Visualization Exploration

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Engineering & Technology

Chemical Engineering
Energy
Engineering
Materials Science

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Formal Sciences

Computer Science
Mathematics

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Health & Medical Sciences

Dentistry
Health Professions
Medicine
Nursing
Pharmacology, Toxicology and Pharmaceutics

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Life Sciences

Agricultural and Biological Sciences
Biochemistry, Genetics and Molecular Biology
Immunology and Microbiology
Neuroscience
Veterinary

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Natural Sciences

Chemistry
Earth and Planetary Sciences
Environmental Science
Physcis and Astronomy

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Social Sciences & Humanities

Arts and Humanities
Decision Sciences
Economics, Econometrics and Finance
Psychology
Social Sciences

Below is a static preview of the hierarchy. An interactive version is coming soon!

Exploration

Click on a core domain below to see its disciplines and subdisciplines:

Overview Knowledge Layers Core Domains Academic Disciplines Visualization Exploration

Engineering & Technology Formal Sciences Health & Medical Sciences Life Sciences Natural Sciences Social Sciences & Humanities