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Reusing and Unifying Background Knowledge for Internet of Things with LOV4IoT


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

Publication Type: 
Refereed Conference Meeting Proceeding
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.
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National University of Ireland, Galway (NUIG)
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