Introduction to Linked data

This training module has been developed within the context of the smeSpire project in 2014 (http://www.smespire.eu/).

Author: Diederik Tirry – KU Leuven. The material is provided under Creative Commons Attribution Share-Alike License (http://creativecommons.org/licenses/by-sa/3.0/).

Linked Data is a web based approach to publish information in a structured way so that it can be interlinked with other information on the web, and thus become more useful. Rather than using web pages for humans to be read, information is presented in such a way that it can be read automatically by computers. This enables data from different sources to be linked and used together. The collection of Semantic Web technologies (RDF, OWL, SKOS, SPARQL, etc.) provides an environment in which applications can query the data, draw inferences using vocabularies, etc. This seminar introduces the main principles of Linked Data, the underlying technologies and background standards. It provides a brief introduction on how data can be published over the Web, how linked data can be consumed, and what are the possible use cases and benefits

This seminar contains the following modules/parts:

1. Introduction to data, information and knowledge
2. Data interoperability and semantics
3. Data heterogeneity and combining data
4. From data to knowledge using inferences

After the training offer, the participant will be able to:
- Identify and describe the concepts of semantic web and linked data
- Explain the difference between linked and open data
- Identify the different steps in publishing linked data
- Understand how linked data can be consumed
- Understand the benefits of linked data

This seminar aims at managers, ICT strategists and professionals that need a basic understanding of Linked Data.