ruc-datalab/EvoOntology

EvoOntology: A Self-Evolving Ontology Layer for Data Agents English | 简体中文 EvoOntology is the first self-evolving ontology layer for data agents, aiming to bridge the agent-data gap over heterogeneous tables, files, and databases. It exposes a versioned Ontology Layer through MCP tools, grounds that layer in real workload evidence, and continuously adapts it from execution trajectories. The Codex and Claude Code plugins build and evolve ontology layers over your data. https://github.com/user-attachments/assets/e15f4acd-7161-4ae1-ba41-f2f3ea05488b An agent-first, self-evolving ontology layer for Data Agents. EvoOntology treats the Ontology Layer as trainable agent state—not model weights. A builder initializes grounded semantic objects from the workload and underlying data; an evolution agent then uses historical interactions to propose bounded updates and validates every Candidate against its Parent. Three interconnected layers define the ontology's knowledge, representation rules, and runtime access: Content Layer: inspect grounded concepts, mappings, constraints, evidence, and their relationships. Click any screenshot to open the full-resolution…