Reusing and Unifying Background Knowledge for Internet of Things with LOV4IoT

Research output: Chapter in Book or Conference Publication/ProceedingConference Publicationpeer-review

Abstract

Ontology-based applications are becoming more and more popular and are usually domain-specific (e.g., eHealth or domotic). Designing ontologies and semantic-based applications manually is tedious and cumbersome for non-technical expert or semantic web beginners. Internet of Things (IoT) is a new field aiming to connect the physical world surrounded by devices such as sensors to the web to automatically interact with them and build innovative applications. The main challenges are to automate as much as possible the tasks of: (1) reusing the background knowledge previously designed by domain experts, (2) facilitating the tasks of IoT developers willing to integrate semantic web technologies into their applications, and (3) designing interoperable semantic-based IoT applications. Stemming from Linked Open Data and Linked Open Vocabularies, we designed Linked Open Vocabularies for Internet of Things (LOV4IoT), a catalogue of ontologies datasets rules relevant for IoT available online. LOV4IoT has been extended with more domains and ontology-based projects, a semantic-based dataset and a bot to enhance automation, and web services. Moreover, we demonstrate several use cases of the LOV4IoT dataset: (1) building Semantic Web of Things applications, (2) extracting frequent terms used in existing ontologies, and (3) stakeholders who can exploit, reuse and combine domain ontologies. Finally, we evaluated this dataset with users who exploit this dataset for their own purposes.
Original languageEnglish (Ireland)
Title of host publication4rd International Conference on Future Internet of Things and Cloud (FiCloud 2016), 22-24 August 2016, Vienna, Austria,
Place of PublicationAustria
Publication statusPublished - 1 Aug 2016

Authors (Note for portal: view the doc link for the full list of authors)

  • Authors
  • Amelie Gyrard, Ghislain Atemezing, Christian Bonnet, Karima Boudaoud, Martin Serrano

Fingerprint

Dive into the research topics of 'Reusing and Unifying Background Knowledge for Internet of Things with LOV4IoT'. Together they form a unique fingerprint.

Cite this