Implicit Ontology Changes Driven by Evolution of e-Health IoT Sensor Data in the τOWL Semantic Framework
Zouhaier Brahmia, Fabio Chiodo Grandi, Abir Zekri, Rafik Bouaziz · 2022
Nowadays, several electronic health (e-Health) systems are using both Internet of Things (IoT) technologies, for remote monitoring of the evolutions of patients states, and ontologies, for interoperability with other similar systems and for conceptualization of the domain of each system. In such environments, instances generated by IoT sensors have to comply with used ontologies. However, some new instances could be structurally inconsistent with respect to the current ontology and consequently require that some changes be applied in order to generate a new ontology version which could consistently accommodate also the new data instances. In this chapter, we first propose an approach that supports ontology changes which are triggered by non-conservative instance updates, giving rise to an ontology schema versioning driven by the arrival of unusual/unexpected instances. Then, we apply this approach to our established semantic framework τOWL (Temporal OWL 2), already proposed for managing the definition of temporal OWL 2 ontologies and their evolution, in a context where both schemas and instances of ontologies are temporally versioned. Finally, as a proof-of-concept of the proposed approach, we developed a new release of our τOWL-Manager tool, which also supports the management of non-conservative ontology instance updates.