PyData Amsterdam 2023

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.