This course provides a practical introduction to ETL (Extract, Transform, Load) for Knowledge Graph construction. It is designed for learners who already understand the basics of RDF and want to learn how to integrate data from sources such as CSV files, databases, JSON, and XML into a unified graph.

We begin by exploring why Knowledge Graphs are used to connect data silos and how ontologies provide the shared semantic model that enables meaningful integration. From there, the course introduces different approaches to graph construction, comparing imperative programming-based pipelines with declarative mapping standards such as RML and YARRRML.

A major focus is on building declarative mappings with YARRRML. You will learn how to create RDF triples from tabular and semi-structured data, work with prefixes, datatypes, language tags, functions, and transformations, and connect multiple data sources into a single graph.

By the end of the course, you will understand how to design scalable Knowledge Graph ingestion pipelines, transform heterogeneous data into RDF, and use industry standards such as YARRRML and RML to create maintainable and interoperable graph solutions.

⌨️ This course contains interactive exercises in our web-based RDF editor!