Historical and archaeological research often involves navigating vast, fragmented, and complex data landscapes. In this talk, we explore how knowledge graphs, powered by Neo4j, can bring structure and insight to these data-rich domains. By modeling relationships across time, geography, artifacts, and historical figures, researchers can uncover hidden connections and validate hypotheses with greater confidence.

The session demonstrates how integrating Neo4j with GenAI enables natural language interfaces and contextual reasoning, making it easier for domain experts to query and interact with historical datasets. Additionally, we’ll introduce the use of Model Context Protocol (MCP) servers to orchestrate semantic enrichment and maintain data integrity across diverse sources.

Whether you’re a technologist, data scientist, or humanities scholar, this session will show how graph technology and AI can collaboratively illuminate the past and drive discoveries.

You can download both the sample code and the presentation from GitHub:

👉 https://github.com/ilich/neo4j-genai-ocre

Feel free to explore the repository and use the materials for your own projects or learning.