MLKN.lab Hierarchy Master File (All Layers, All Details)

A comprehensive dataset for MLKN.lab's polyhierarchical knowledge network, containing all layers and details of the hierarchy. MLKN.lab (Multi-Layered Knowledge Network Ideas Laboratory): URL: https://francoispapin.github.io/MLKN-lab/ # MLKN.lab Hierarchy Master File (All Layers, All Details) (Version: v1.0) This dataset is the **core hierarchy file** for **MLKN.lab (Multi-Layered Knowledge Network Ideas Laboratory)**, a research project that models **scientific knowledge as a polyhierarchical hypergraph**. The file contains the **complete, multi-layered hierarchy** of scientific domains, subdomains, topics, and concepts, extracted from **OpenAlex** and structured for **network analysis, visualization, and computational epistemology**. --- ## **Dataset Overview**- **Format**: CSV (Comma-Separated Values)- **Size**: 94.2 MB- **Rows**: [Insert number, e.g., ~500,000]- **Columns**: [Insert number, e.g., 10]- **Layers**: 5 ontological layers (Core Domains → Fields → Subfields → Topics → Concepts)- **Source**: All data are derived from OpenAlex. [OpenAlex API](https://openalex.org/) (free, open catalog of scholarly papers)- **Last Updated**: June 2026 --- ## **Intended Use Cases**This dataset is designed for:1. **Network Analysis**: - Study the **topological structure** of scientific knowledge (e.g., using [NetworkX](https://networkx.org/), [igraph](https://igraph.org/), or [Gephi](https://gephi.org/)). - Identify **key disciplines, bridges between fields, or emerging research areas**.2. **Knowledge Graph Visualization**: - Build **interactive visualizations** of the hierarchy (e.g., using [D3.js](https://d3js.org/), [Cytoscape.js](https://js.cytoscape.org/), or [Plotly](https://plotly.com/)). - Explore **polyhierarchical relationships** between domains.3. **Meta-Science Research**: - Analyze **interdisciplinarity, knowledge diffusion, or the evolution of scientific fields**. - Study **how disciplines connect, overlap, or diverge** over time.4. **Computational Epistemology**: - Model **how knowledge is structured, validated, and evolved** in computational systems. - Develop **AI systems** that reason over scientific knowledge. --- ## **Related Resources**- **MLKN.lab Website**: [https://francoispapin.github.io/MLKN-lab/](https://francoispapin.github.io/MLKN-lab/) Explore the **project’s mission, methodology, and applications**.- **Scientific References**: [https://francoispapin.github.io/MLKN-lab/references/references.html](https://francoispapin.github.io/MLKN-lab/references/references.html) A **curated bibliography** of 165+ references that inspire MLKN.lab.- **GitHub Repository**: [https://github.com/FrancoisPapin/MLKN-lab](https://github.com/FrancoisPapin/MLKN-lab) Access the **code, smaller datasets, and documentation** for MLKN.lab. ---## **Citation**If you use this dataset, please cite it as: Papin, F. (2026). MLKN.lab Hierarchy Master File (All Layers, All Details) [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.20829289 For detailed usage instructions, see the [README.md](README.md) file attached to this deposit.