Ontology Creation
summary
Builds a graph schema from messy HTML and structured CSVs using the Data Modeling MCP server and Claude Desktop, producing a JSON model that the server validates against a pydantic schema, flags duplicate properties, ensures source/target nodes, and generates a mermaid visualization. The model then augments with London tube stations, the system emits OWL (Turtle) and Cypher ingest code, requires no DB connection to run, and the end-to-end conversion and export complete successfully.
AI-written summary · about
chapters (9)
- 0:00Introduction to speakers
- 0:27What is an ontology
- 3:17Worked example plan
- 5:24Workflow with MCP server
- 9:20Creating blue plaques model
- 14:24Augmenting with tube data
- 18:44Exporting to OWL ontology
- 23:00Iterative modeling approach
- 26:13Open source call to action
related talks
02h 27mKnowledge graph data modelling with TerminusDB
30mContext Engineering: Connecting the Dots with Graphs
15mEasy Metadata Management (Git for Data) Using Neo4j
35mUsing Semantic Metadata to Create an Automated Microservice Data Mesh
44mBuilding Knowledge Graphs
36mVibing with Data -- Multi-Agent Data Modeling and Constructi...
51mTime to graph up with Spring Data Neo4j
52mWhat the Graph