Ontology for experimentation of human-building interactions using virtual reality. (January 2023) - Chokwitthaya, Chanachok; Zhu, Yimin; Lu, Weizhuo
Graphical abstract: Highlights: An ontology to describe virtual building experiments was proposed as VHBIEO. Several concepts were reused from existing ontologies and semantic models, namely the ontology of scientific experiments (EXPO), the spatial–temporal event-driven model (STED), the ontology to represent energy-related occupant behavior in buildings (DNAs), the ifcOWL ontology (ifcOWL), the semantic sensor network ontology (SSN), the survey ontology (SUR), and the units of measurement ontology (UO). DOGMA approach was applied to establish the internal structure of VHBIEO, involving an ontology base and ontological commitments. Taxonomy and application evaluations demonstrated efficacy of VHBIEO. Abstract: Scientific experiments significantly enhance the understanding of human-building interactions in building and engineering research. Recently, conducting virtual reality (VR) experiments has gained acceptance and popularity as an approach to studying human-building interactions. However, little attention has been given to the standardization of the experimentations. Proper standardization can promote the reusability, replicability, and repeatability of VR experiments and accelerate the maturity of this emerging experimentation method. Responding to such needs, the authors proposed a virtual human-building interaction experimentation ontology (VHBIEO). It is an ontology at the domain level, extending the ontology of scientific experiments (EXPO) to standardize virtual human-building interaction experimentation. It was developed based on state-of-the-art ontology development approaches. Competency questions (CQs) were used to derive requirements and regulate the development. Semantic Web technologies were applied to make VHBIEO machine-readable, accessible, and processable. VHBIEO incorporates an application view (APV) to support the inclusion of unique information for particular applications. The authors performed taxonomy evaluations to assess the consistency, completeness, and redundancy, affirming no occurrence of errors in its structure. Application evaluations were applied for investigating its ability to standardize and support generating of machine-readable, accessible, and processable information. Application evaluations also verified the capability of APV to support the inclusion of unique information.