Semantic Modeling of Trustworthy IoT Entities in Energy-Efficient Cultural Spaces.

In this paper, an ontology related to energy-efficient cultural spaces is presented. Specifically, this research work concerns ongoing efforts towards engineering the Museum Energy-Saving Ontology (MESO) towards meeting the following objectives: a) to represent knowledge related to the trustworthy IoT entities that are deployed in a museum i.e., things (e.g., exhibits, spaces), sensors, actuators, people, data, applications; b) to deal with entities’ heterogeneity via semantic interoperability and integration, especially for ’smart’ museum applications and generated data; c) to represent knowledge related to saving energy e.g., lights, air-conditioning; d) to represent knowledge related to museum visits and visitors towards enhancing visiting experience while preserving comfort; e) to represent knowledge related to environmental conditions towards protecting and preserving museum artwork via continuous monitoring. The human-centered collaborative, agile and iterative methodology is followed, namely HCOME, towards the development of an evolved, ‘live’ and modular ontology, while SWRL rules and SPARQL queries are used for its preliminary evaluation.