OWL 2 modeling and reasoning with complex human activities

Abstract

In recent years, there has been a growing interest in the adoption of ontologies and ontological reasoning to automatically recognize complex context data such as human activities. In particular, the Web Ontology Language (OWL) emerged as the language of choice, being a standard for the Semantic Web, and supported by a number of tools for knowledge engineering and reasoning. However, the limitations of OWL 1 in terms of expressiveness have been recognized in various fields, and important research e↵orts have been made to extend the language while preserving decidability of its OWL 1 DL fragment. The result of such work is OWL 2. In this paper we investigate the use of OWL 2 for modeling complex activities and reasoning with them. We show that the new language constructors of OWL 2 overcome the main limitations of OWL 1 for the representation of activities; OWL 2 axioms can be used to represent certain rules and rule-based reasoning previously demanded to hybrid approaches, with the advantage of having a unique semantics, avoiding potential inconsistencies. Then, we propose a system architecture showing the integration of a novel OWL 2 activity ontology and reasoning modules with distributed modules for sensor data aggregation and reasoning. The feasibility of our solution is shown by an extensive experimental evaluation with simulations of di↵erent intelligent environments.

Survey of context information fusion for ubiquitous Internet-of-Things (IoT) systems

“…OWL has developed into a standard for semantic web, and is supported by a number of tools for knowledge engineering and reasoning. In [89] various solutions are shown using extensive experimental evaluation and simulations for di erent intelligent environments using speci cally OWL2. OWL2 language constructs are apt for activity representation; its axioms can be used to represent certain rules and rule-based reasoning in hybrid approaches having unique semantics by avoiding inconsistencies.…”

PO-SAAC: A Purpose-Oriented Situation-Aware Access Control Framework for Software Services

“…In the present age, ontology-based modeling technique has been proven as a suitable logical language for modeling dynamic contexts/situations (e.g., [12], [13]). The ontology-based modeling approach to achieve situation-awareness (e.g., [7], [8]) is not only beneficial from the representational viewpoint but also beneficial from the reasoning viewpoint; that is, once facts about the world is stated in terms of the ontology, other facts can be inferred using the inference engine through the inference rules.…”

“…To model the PO-SAAC ontology, in this paper, we adopt the OWL language as an ontology language to represent the situations, which has been the most practical choice for most ontological applications because of its considered tradeoff between computational complexity of reasoning and expressiveness [13]. In order to support the process of inferring new composite situations, we need to define a set of reasoning rules that are associated with the existing or already defined situations.…”

Combining ontological and temporal formalisms for composite activity modelling and recognition in smart homes

“…The use of ontologies in activity modelling and activity recognition has spurred interest but the focus has largely been on simple activities [9,10,31]. Ontological activity modelling can be used to define activity ontologies that describe activities and their characteristics [9,10].…”