Giuseppe Futia, CSI - Piedmontese Consortium for Information Systems (Italy), Data Engineer

Knowledge Graphs (KGs) are essential for data integration and analytics, yet selecting the right technology stack remains challenging. While Label Property Graphs (LPG) enable the usage of powerful graph-based algorithms, Resource Description Framework (RDF) provides robust data interoperability, constraints, and reasoning. This hands-on tutorial guides participants in building a hybrid KG system that combines LPG and RDF, leveraging their strengths.

Using real-world open data from the City of Chicago—including business activities, licenses, organizations, and contracts—participants will address key governance and financial transparency challenges:

Entity Resolution & Financial Tracking: Connecting datasets to trace financial transactions and identify money flows for a unique entity.
Conflict of Interest Detection: Uncovering hidden relationships between businesses and financial transactions to flag ethical and regulatory concerns.
Regulatory Compliance & Risk Assessment: Detecting inconsistencies between contracts and assigned licenses by validating activities against constraint-based rules.
Additionally, the tutorial will show how LLMs enhance the interaction with the KG system, enabling intuitive exploration. By the end, attendees will gain hands-on experience integrating LPG and RDF while leveraging LLMs for insightful KG analysis.

This session is ideal for practitioners and researchers applying a hybrid, AI-powered KG approach to real-world problems.