Data Information Interoperability Model for IoT-enabled Smart Water Networks

Abstract

Syntactic and semantic interoperability is a fundamental requirement for the success of the Internet of Things (IoT)-enabled Smart Water Networks (SWNs). Still, whilst consuming publicly accessible IoT data, the syntactic and semantic representation of the collected data poses challenges for the success of pervasive and ubiquitous sensing in the water domain.Challenges include the heterogeneity of data representation formats, semantic models, and the adoption of domain-specific standards and ontologies. These challenges emphasise the requirement for enhanced interoperability in SWNs. To address this, we propose a Data and Information Interoperability Model (DIIM) by combining the Semantic Web technologies, widely known for overcoming interoperability issues, and Model-driven architecture (MDA) approach. DIIM facilitates syntactic interoperability by serialization conversion and adoption of domainspecific standards as well as semantic interoperability of metadata by aligning the semantic models of IoT and Smart Water Network (SWN) applications. Furthermore, it automatically creates an ontology as a semantic model if it is missing and adds references to existing domain-specific ontologies as annotation in their models. We evaluate DIIM methodology by applying it to a real-world use case of IoT-enabled applications for water quality monitoring.