AUGMANITAI Knowledge Graph V2 Snapshot — 79 Phenomena Force-Directed Visualization with AI Discovery Metadata (Restricted)
Year: 2026
Type: article
Abstract: Restricted dated snapshot of the AUGMANITAI Knowledge Graph live publication as of 2026-05-02, comprising nine files. The bundle contains a force-directed graph HTML visualization of 79 curated interaction phenomena with edges representing conceptual relations, alongside machine-readable discovery assets: llms.txt, .well-known-ai.txt, .well-known-llms.txt, CITATION.cff, robots.txt, and sitemap.xml. Domains and fields covered include human-AI interaction research, knowledge graph visualisation, graph topology, computational phenomenology, semantic web standards, LLM discoverability infrastructure, citation metadata, and AI crawler compliance. The visualization reflects the same 79 phenomena as Atlas V2, post-audit. Part of the NEOMANITAI / AUGMANITAI research programme by Andreas Ehstand (independent researcher; ORCID 0009-0006-3773-7796). Descriptive ISO-704-style terminology; research-only; not a clinical, therapeutic, or normative tool. Methodological mechanics and operating procedures are held under restricted access. License: CC BY-NC-ND 4.0. Living document; prepared with AI assistance.
Author: Ehstand, Andreas
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7160395859
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