Introduction to Knowledge Graphs Training Programme

Learning Outcomes

In this course, the participant will learn how to:

• Write semantic queries using SPARQL
• Share your data and its descriptions
• Think about the meaning of data in new ways
• Use the power of RDF to represent any information
• Effortlessly integrate data from multiple sources
• Leverage proven W3C standards to deliver advanced capabilities with a non-proprietary solution

Course Outline

History of Data Processing

• Data challenges facing many organisations today
• Representing Data as Tables
• The Relational Model
• Identifying Data
• Knowledge graph representation

Resource Description Framework (RDF)

• What a graph is and how it compares to tabular data
• Uniquely Identifying Data: IRIs and CURIEs
• RDF Serialisations: N-Triples and Turtle
• Named Graphs and serialisations: N-QUADS and TriG

Querying Knowledge Graphs with SPARQL

• ASK queries
• Pattern Matching
• SELECT queries
• Type and Class
• FILTER clause
• DISTINCT keyword
• ORDER BY clause
• LIMIT clause
• CONSTRUCT queries

Knowledge Graph Metadata

• What is metadata?
• RDF Metadata
• RDF Schema (RDFS)
• Web Ontology Language (OWL)
• Simple Knowledge Organisation System (SKOS)
• Shape Constraint Language (SHACL)

Knowledge Graph Architecture

• Triple Store and SPARQL Engine
• Inferencing Engine
• Data Ingestion
• Data Federation
• Data Virtualisation
• Data Visualisation
• FAIR data principles