RDF Graph Models for Global Data Integration

In a world of disconnected databases, merging data from different sources often leads to costly and fragile integration projects. The Resource Description Framework (RDF) provides a standardized, graph-based approach to link and share data globally without complex schema mappings. This text-based course guides you from the fundamental concepts of semantic web technology to designing and querying unified data graphs. You will learn how to represent relationships, assign global identifiers, and prepare your data for automated reasoning and integration. What you'll learn: - Understand the core architecture of RDF, including triples, URIs, and graph structures - Write and read standard serialization formats such as Turtle and JSON-LD - Query distributed graph data efficiently using basic SPARQL syntax - Apply ontologies and schema vocabularies to establish shared meaning across datasets - Leverage basic inference rules to discover hidden relationships within your data - Design integration strategies to merge disparate data sources into a unified knowledge graph You will start with foundational definitions and key semantic web terminology before exploring practical data modeling patterns. The course then walks you through querying techniques and real-world integration strategies to build scalable, connected data architectures. This course is designed for beginner data analysts, software developers, and database administrators who want to learn semantic data integration from the ground up, with no prior experience in graph databases required. Start reading today to unlock the power of globally connected graph data.