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Linked Data, Solid and interoperable dataspaces

More and more data is generated by an increasing number of agents (applications and devices) that are connected to the Internet, all contributing to data that is available on the Web. When this data is analyzed, combined, and shared powerful, new techniques can be designed and deployed, such as artificial intelligence applied by personal assistants (e.g., Apple's Siri and Amazon Alexa), improved search engines (e.g., Google Search and Microsoft's Bing), and decentralized data storages (as opposed to a large, central storage used by big companies).

Due to this increase in data, methods originally used to model data have become insufficient: they isolate the data, which resides in different data sources, and make it hard for agents to exchange data on the Web. Data cannot be easily exchanged between agents, because every agent uses a different data model to describe the concepts and relationships of the data they generate and use.

Linked Data and Solid offer a solution to this problem. Linked Data provides semantic descriptions of entities and their relationships, materialized via RDF. Solid is a specification that allows users to store this data securely in decentralized stores. When data is stored in a pod, the user controls which people and applications can access it.

This course teaches you:

  • A basic understanding of Linked Data
  • A basic understanding of Solid
  • A basic understand of semantic reasoning and streaming
  • How to publish Linked Data (in Solid pods)
  • How to create queries over Linked Data (in Solid pods)
  • How to design and publish Linked Data vocabularies
  • How to generate Linked Data from non-Linked Data using RML.io
  • How to create interoperable Linked Data in Flanders and Europe
  • How to create a Linked Data architecture using Linked Data Fragments and Linked Data Event Streams
  • How to validate Linked Data using SHACL and ShEx

Practical information

The first lesson on 25 September 2025 and the last session on 18 December 2025 are given onsite from 17h30 till 21h.

For the other lessons there will be a teams meeting of 1 hour each week (20h – 21h) where questions on the theory and the solutions of the exercises will be discussed. Per lesson participants must provide 4 hours of preparation time during the week: they have to watch the recordings of the theory independently and also submit an exercise.

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