"Knowledge Graphs, in Principle and Practice" is designed to provide a comprehensive graduate-level understanding of knowledge graphs (KGs), ranging from their mathematical foundations to industrial-scale implementation and ethical governance.

Module I: Foundations & Formalisms

The course begins with the formal definition of a knowledge graph as a structured data model representing information as a network of interconnected entities (V) and their relationships (R).

Mathematical Representation: Defining graphs as G=(V,E,R) and understanding the fundamental unit of knowledge: the semantic triple (Subject → Predicate → Object).

The Blueprint: Distinguishing between the TBox (Terminological Box), which defines the schema and rules, and the ABox (Assertional Box), which contains the factual assertions.

Architectural Paradigms: Comparing RDF (Resource Description Framework) for web-scale logic and LPG (Labeled Property Graph) for high-performance analytics.

Description Logics (DL): Analyzing the trade-offs between expressive power and computational tractability in various OWL 2 profiles (EL, QL, RL)