Tutorial: Semantic web techniques meet sensor data

Tutorial: Semantic web techniques meet sensor data

14th International Conference on Intelligent Environments (IE'18) 25-28 of June 2018, Rome - Italy http://www.intenv.org/

Semantic Web technologies have been gaining traction in the last decade as an important tool to enable data interoperability. They allow to represent, interlink, publish,query, and reason with heterogeneous data. The data is described using ontologies, formal definitions of the types of the entities that exist in the domain, and of relations that link them. Ontologies give formal semantics to the data, which allows for data exchange with shared and unambiguous meaning, logical reasoning, and data discovery. In addition, the Linked Data principles portray guidelines to publish semantic data on the Web, based on semantic web technologies, to ease the discoverability and reuse of data. Semantic Web technologies are used in a variety of fields, including intelligent environments, healthcare, life sciences, linguistics, and cultural heritage, among other. Ontologies are also present in industry whenever interoperability or heterogeneous data integration is required. Examples include knowledge graphs in large corporations, such as Google, Facebook, IBM, Adobe, or Yahoo. The goal of this tutorial is to present the basics on Semantic Web technologies, and Linked Data principles and best practices. The tutorial assumes no prior knowledge on the topics, and can serve as an introduction for people interested in attending the tutorial "Choosing your ontologies for sensor data applications."

Duration: 1h30

José M. Giménez-García, Université Jean Monnet, Saint-Étienne, France

José M. Giménez-García, M.Sc., is a Ph.D. student at Université Jean Monnet and member of Laboratoire Hubert Curien. He worked before as software developer and analyst at Everis and Fundación Ayuda en Acción. He developed HDT-MR, a tool to compress huge RDF datasets into a binary representation that retains query capabilities. His current research interest is representation and management of complex relations and metadata in the Semantic Web.


  • Historical Background.
  • Representing Statements: Resource Description Framework (RDF)
  • Describing the Structure: RDF-Schema (RDFS).
  • Giving Semantics: Web Ontology Language (OWL)
  • Querying: SPARQL
  • Publishing and Interconnecting: Linked Data