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Linked

Data

Explore Semantic Web concepts, linking data meaningfully for smarter applications and improved search.

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Course Detail

The Linked Data course explores the fundamentals of Linked Data and how it is used to structure and connect information on the web.

Course Features

  • Introduction to Linked Data.
  • Linked data principles.
  • RDF – The Data Model.
  • Querying Linked Data.
  • Applications & Best Practices.

Lexsense

Language Engineer

Chakir Mahjoubi is a Language Engineer specialising in NLP and ontology-based systems for knowledge representation.

  • 4 Weeks · 16 Lessons 3~6 hrs total
  • Beginner–Intermediate
  • Access on Mobile and PC

Course Content

11 sections • 28 lecture • 19h 33m total length

Linked Data is a method of publishing structured data on the web so that it can be connected, shared, and reused across different systems. It is a key part of the broader vision of the Semantic Web, which aims to make web data understandable not just by humans, but also by machines.

The Linked Data principles are a set of foundational rules that guide how data should be published on the web so it can be easily connected, shared, and reused.

RDF (Resource Description Framework) is the core data model of Linked Data. It provides a standard way to represent information as a graph of relationships, rather than as tables (databases) or documents (web pages).

SPARQL is used to query and manipulate RDF datasets efficiently. It allows retrieval of structured data using flexible query patterns. Learners explore basic and advanced query operations on semantic data. 

Linked Data is used in knowledge graphs, search engines, open data, and enterprise systems to integrate and enrich information across diverse sources.

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