Managing Connected Big Data in Art with Neo4j Graph Database
summary
Models Wikipedia into a property graph using Neo4j + Cypher, imports English Wikipedia into roughly 16 million nodes and about 200 million relationships, and shows traversal speed benefits because relationships are stored not computed. Builds an art graph linking artists, artworks, cities and colors, runs color- and geospatial-queries, and prototypes a mobile recommender. Uses Neo4j import tools, JDBC/bolt connectors and a geospatial plugin; claim: relationship-first modeling reveals unexpected artist-color and influence patterns and scales to real-world datasets.
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chapters (11)
- 0:00Introduction to connected data
- 1:47Modern data management overview
- 5:09Why relational databases fail
- 12:52Graph databases vs NoSQL
- 17:29Neo4j and graph theory basics
- 22:34Art data project introduction
- 26:50Importing Wikipedia into graph
- 29:07Querying artist relationships
- 33:10Adding geospatial data
- 36:00Color analysis with Wikipedia
- 39:53Q&A and closing
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