PyData Amsterdam 2023

Mastering Knowledge Graph Modeling with Neo4j: A Practical Tutorial
09-15, 13:00–14:30 (Europe/Amsterdam), Hello, World! (Tutorials)

This hands-on tutorial introduces participants to knowledge graph modeling using Neo4j, a popular graph database. Suitable for beginners and those seeking to enhance their knowledge, the tutorial will help attendees to learn the fundamentals of knowledge graphs, gain insights into Neo4j's modeling capabilities, and acquire practical skills in designing effective knowledge graph models.

In this tutorial, we'll explore knowledge graphs and their modeling using Neo4j, a popular graph database. Participants will learn effective modeling techniques and how to leverage this technology for their own projects.

The tutorial is for data professionals, data scientists, software engineers, and anyone interested in knowledge graphs. No prior experience with Neo4j or knowledge graph modeling is required, making it suitable for beginners and those looking to expand their knowledge.

The tutorial will be interactive, combining theory and practical exercises to provide a comprehensive understanding of knowledge graph modeling. The tone will be informative and engaging, encouraging active learning and collaboration.

By the end of this tutorial, participants will:

  1. Understand the concept of knowledge graphs and their significance in representing complex relationships and interconnected data.
  2. Gain familiarity with Neo4j and its capabilities for knowledge graph modeling.
  3. Acquire knowledge of representation patterns, best practices, pitfalls to avoid, and trade-offs to consider when modeling knowledge graphs.
  4. Develop practical skills through hands-on exercises and examples, enabling them to apply knowledge graph modeling techniques to their own projects.

Tentative schedule:

  1. Introduction to Knowledge Graphs (20 minutes)
    - Definition and real-world applications of knowledge graphs
    - General and common knowledge graph elements

  2. Introduction to Neo4j (15 minutes)
    - Overview of Neo4j as a graph database
    - Understanding Neo4J’s graph data model and the Cypher language

  3. Representing knowledge graphs in Neo4J (20 minutes)
    - Understanding different patterns for modeling entities, relations and other knowledge graph elements
    - Choosing the appropriate pattern based on data and application requirements
    - Avoiding common mistakes and pitfalls
    - Making informed decisions about common dilemmas and trade-offs

  4. Hands-on Exercise (20 minutes)
    - Guided exercise to model a knowledge graph using Neo4j

  5. Q&A and Discussion (10 minutes)
    - Addressing participant questions and engaging in interactive discussion

  6. Wrap-up and Conclusion (5 minutes)
    - Recap of key concepts and takeaways from the tutorial
    - Suggestions for further learning and resources

All materials, including code examples, exercises, and supplementary resources, will be made available through a dedicated GitHub repository. Participants can access and download these materials to continue their learning journey beyond the tutorial session.

Prior Knowledge Expected

No previous knowledge expected

Panos Alexopoulos has been working since 2006 at the intersection of data, semantics, and software, contributing to building intelligent systems that deliver value to business and society. Born and raised in Athens, Greece, he currently works as Head of Ontology at Textkernel, in Amsterdam, Netherlands, where he leads a team of Data Professionals in developing and delivering a large cross-lingual Knowledge Graph in the HR and Recruitment domain.

Panos holds a PhD in Knowledge Engineering and Management from National Technical University of Athens, and has published more than 60 papers at international conferences, journals and books. He is the author of the book "Semantic Modeling for Data - Avoiding Pitfalls and Breaking Dilemmas" (O'Reilly, 2020), and a regular speaker and trainer in both academic and industry venues.