Neo4j is your RDF store (part 3) : Thomson Reuters’ OpenPermID

If you’re new to RDF/LPG, here is a good introduction to the differences between both types of graphs.  
For the last post in this series, I will work with a larger public RDF dataset in Neo4j. We’ve already seen a few times that importing an RDF dataset into Neo4j is easy, so what I will focus on in this post is what I think is the more interesting part, which is what comes after the data import, here are some highlights:

  1. Applying transformations to the imported RDF graph to make it benefit from the LPG modelling capabilities and enriching the graph with additional complementary data sources.
  2. Querying the graph to do complex path analysis and use graph patterns to detect data quality issues like data duplication and also to profile your dataset
  3. Integrate Neo4j with standard BI tools to build nice charts on the output of Cypher queries on your graph.
  4. Building an RDF API on top of your Neo4j graph.

All the code I’ll use is available on GitHub. Enjoy!

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