Building energy performance assessment using linked data and cross-domain semantic reasoning

Shushan Hu (Corresponding author), Jiale Wang, Cathal Hoare, Yehong Li, Pieter Pauwels, James O'Donnell (Corresponding author)

Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

7 Citaten (Scopus)
94 Downloads (Pure)


Cross-domain information is essential for building energy performance assessment. The heterogeneous nature of this information is a major source for inefficient assessments. The semantic web provides a flexible pathway for addressing recognised interoperability issues. However, further implicit knowledge in cross-domain information could provide meaningful solutions for such assessments. This paper aims to develop a conceptual framework that links cross-domain information, infers implicit knowledge, and empowers building managers with insightful assessments. The framework integrates Web Ontology Language (OWL) ontologies, Resource Description Framework (RDF) instances, and a set of predefined rules to infer implicit knowledge, which can satisfy data requirements of performance metrics and enable meaningful performance assessments. Then building managers can identify inefficient building operations and improve energy efficiency while maintaining desired building functions. This approach reduces burdensome intervention from the managers when compared with traditional solutions. A demonstration highlights the engineering value by evaluating energy performance of a university building.
Originele taal-2Engels
Aantal pagina's13
TijdschriftAutomation in Construction
StatusGepubliceerd - apr. 2021


Duik in de onderzoeksthema's van 'Building energy performance assessment using linked data and cross-domain semantic reasoning'. Samen vormen ze een unieke vingerafdruk.

Citeer dit