uCSN: An Ontology for user-Context Modeling in Sensor Networks

Approach Overview

Context-awareness has emerged as a key paradigm for ubiquitous computing and ambient intelligence applications (e.g., IoT-based applications). This paradigm leverages situational information about people and their environments to better improve the quality of machine-to-human communications. Semantic Web techniques (e.g., ontologies) have been recently adopted as the most suitable modeling formats to deal with the heterogeneity of context information. However, existing works do not fully address the challenges of: (i) covering the modeling of domain independent information that describe the user profile, activity, and environments (connected/non-connected); (ii) representing diverse types of data sources from which information is collected; (iii) representing information with different types and formats; (iv) representing uncertainty aspects of captured information; and (v) providing a generic and modular model to allow re-usability in various application domains. Consequently, we propose uCSN, a generic and modular ontology for user-Context modeling in Sensor Networks. This ontology was previously called SUEM for Semantic User Environment Modeling. uCSN provides a complete view of the user context by introducing new concepts/properties and borrowing others from existing well-known ontologies such as Data Privacy Vocabulary (DPV), Semantic Sensor Network (SSN), Hybrid SSN (HSSN), and Uncertainty Ontology. Therefore, uCSN is able to cover the representation of all domain independent context information. We evaluate the accuracy, clarity, performance, and consistency of uCSN. Results show that our ontology can be used by various context-aware systems in different application domains, including those requiring high quality of information coverage (e.g., privacy-preserving systems) or/and real-time reasoning.

uCSN Ontology

Research Areas

  • Context-aware Computing
  • Ontology
  • Context Modeling
  • Semantic Sensor Network
  • Data Privacy Vocabulary
  • Internet of Things

PhD Student

Karam Bou Chaaya

Project Members

  • Richard Chbeir
  • Philippe Arnould
  • Mahmoud Barhamgi
  • Djamal Benslimane

Ontology Files