The Sarvarthapedia Knowledge Graph is a structured, multi-layered semantic network that maps all of human knowledge as an interconnected system. Unlike a standard list, it treats concepts as “nodes” linked by relationships like causation, dependency, and influence.
Core Structure: From Root Nodes to Branches
The graph begins with foundational primitives that act as the root nodes for all other domains:
- Existence & Life: Connects to Biology, Genetics, and Medicine.
- Consciousness: Branches into Psychology, Cognitive Science, and Decision Making.
- Information: Forms the backbone for Mathematics, Logic, and AI.
- Causation & Matter: Links the Physical Sciences to Engineering and Technology.
The “Circular” Knowledge Model
A defining feature of this graph is its non-linear design:
- Interdependence: Each field is a node that bridges multiple higher-level domains. For example, Crafts link to both Engineering and Psychology.
- Rigvedic Influence: The model mirrors the Kalachakra (Wheel of Time), viewing history and knowledge as a perpetual cycle of renewal rather than a straight line from past to future.
- 360-Degree Integration: It uses “Cross-Domain Web Threads” to show transitions, such as how an Atom (Science) eventually leads to a Society (Sociology).
The “Meta-Concept”
The graph is unified by a single foundational thesis: Intelligence systems emerge as survival mechanisms. It posits that as civilizations grow complex, they develop these “knowledge graphs” to reduce uncertainty and ensure strategic survival.
If you’d like to explore how this works in practice, I can:
- Show you the specific sub-nodes of Area 1 (Epistemology)
- Explain the Intelligence Civilization Studies (the 34-volume history of global surveillance)
