Transitioning Obsidian into an Ontology-Based Database for AI Agents
A new concept proposes transitioning Obsidian from a traditional data storage and search tool into an ontology-based database. This shift is designed to enable AI agents to fully comprehend the complex relationships between different data points. Standard knowledge bases often limit AI agents to simple keyword searches, whereas an ontological structure allows agents to reason about data connections. This could significantly improve the autonomy and collaboration of AI agents working within a shared knowledge base. The concept shifts the focus of Obsidian from a personal "second brain" for human retrieval to a structured database designed for machine readability. By defining formal categories, properties, and relations, AI agents can navigate and utilize the stored knowledge more effectively.
## BACKGROUND
Obsidian is a popular markdown-based note-taking application often used for personal knowledge management. In information science, an ontology is a formal representation of categories, properties, and relationships between concepts within a domain. Integrating ontologies into databases helps systems perform semantic reasoning rather than just text matching.