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

Hu, Shushan; Wang, Jiale; Hoare, Cathal; Li, Yehong; Pauwels, Pieter; O’Donnell, James

doi:10.1016/j.autcon.2021.103580

Cited by 34 publications

(16 citation statements)

References 52 publications

(81 reference statements)

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“…The performance assessment is then often executed in a dedicated software layer that uses SPARQL results and time-series data [40]. Both Hu et al [42] and Donkers et al [22] used this principle to assess energy performance and indoor environmental quality, respectively.…”

Section: Semantic Web Technologies For Building Performancementioning

confidence: 99%

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Creating occupant-centered digital twins using the Occupant Feedback Ontology implemented in a smartwatch app

Donkers

Vries

Yang

2024

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Occupant feedback enables building managers to improve occupants’ health, comfort, and satisfaction. However, acquiring continuous occupant feedback and integrating this feedback with other building information is challenging. This paper presents a scalable method to acquire continuous occupant feedback and directly integrate this with other building information. Semantic web technologies were applied to solve data interoperability issues. The Occupant Feedback Ontology was developed to describe feedback semantically. Next to this, a smartwatch app – Mintal – was developed to acquire continuous feedback on indoor environmental quality. The app gathers location, medical information, and answers on short micro surveys. Mintal applied the Occupant Feedback Ontology to directly integrate the feedback with linked building data. A case study was performed to evaluate this method. A semantic digital twin was created by integrating linked building data, sensor data, and occupant feedback. Results from SPARQL queries gave more insight into an occupant’s perceived comfort levels in the Open Flat. The case study shows how integrating feedback with building information allows for more occupant-centric decision support tools. The approach presented in this paper can be used in a wide range of use cases, both within and without the architecture, building, and construction domain.

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Section: Semantic Web Technologies For Building Performancementioning

confidence: 99%

“…Hu et al [42] and Donkers et al [22] stored performance metrics in an RDF format to evaluate building performance. Their work is based on ontologies previously developed by Hu et al [40,41] and Corry et al [17].…”

Section: Semantic Web Technologies For Building Performancementioning

confidence: 99%

Creating occupant-centered digital twins using the Occupant Feedback Ontology implemented in a smartwatch app

Donkers

Vries

Yang

2024

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“…Despite the matching techniques and approaches, the ontology matching is crucial to improve the integration of different datasets and the development cross-domain information environment. Recent implementation of the cross-domain building information using semantic web technologies have shown a great success in the AEC sector (Hu et al, 2021). Accordingly, cross-domain information between the H&S silo datasets and the BIM environment (mainly IfcOWL) can significantly improve the design for safety process.…”

Section: Ontology Matchingmentioning

confidence: 99%

Construction safety ontology development and alignment with industry foundation classes (IFC)

Farghaly¹,

Soman²,

Collinge³

et al. 2022

ITcon

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A pronounced gap often exists between expected and actual safety performance in the construction industry. The multifaceted causes of this performance gap are resulting from the misalignment between design assumptions and actual construction processes that take place on-site. In general, critical factors are rooted in the lack of interoperability around the building and work-environment information due to its heterogeneous nature. To overcome the interoperability challenge in safety management, this paper represents the development of an ontological model consisting of terms and relationships between these terms, creating a conceptual information model for construction safety management and linking that ontology to IfcOWL. The developed ontology, named Safety and Health Exchange (SHE), comprises eight concepts and their relationships required to identify and manage safety risks in the design and planning stages. The main concepts of the developed ontology are identified based on reviewing accident cases from 165 Reporting of Injuries, Diseases and Dangerous Occurrences Regulations (RIDDOR) and 31 Press Releases from the database of the Health and Safety Executive (HSE) in the United Kingdom. Consequently, a semantic mapping between the developed ontology and IfcOWL (the most popular ontology and schema for interoperability in the AEC sector) is proposed. Then several SPARQL queries were developed and implemented to evaluate the semantic consistency of the developed ontology and the cross-mapping. The proposed ontology and cross-mapping gained recognition for its innovation in utilising OpenBIM and won the BuildingSMART professional research award 2020. This work could facilitate developing a knowledge-based system in the BIM environment to assist designers in addressing health and safety issues during the design and planning phases in the construction sector.

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“…In AEC contexts, linked data and graph-based technologies can boost digitalization and knowledge creation [ 40 ], and a few studies have explored these potentials. Research efforts have developed semantic web- and graph-based applications to improve processes in quality management and defect prevention [ 16 ], construction procurement [ 41 ], asset management [ 42 ], building energy performance management [ 43 ], knowledge management [ 44 ], and look-ahead planning [ 45 ]. While linked data have been used to improve interoperability and link across domains in AEC research [ 46 ], scholarly efforts have barely delved into the potentials for construction safety information sharing.…”

Section: Literature Reviewmentioning

confidence: 99%

Data-Driven Construction Safety Information Sharing System Based on Linked Data, Ontologies, and Knowledge Graph Technologies

Pedro

Pham-Hang

Nguyen

et al. 2022

IJERPH

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Accident, injury, and fatality rates remain disproportionately high in the construction industry. Information from past mishaps provides an opportunity to acquire insights, gather lessons learned, and systematically improve safety outcomes. Advances in data science and industry 4.0 present new unprecedented opportunities for the industry to leverage, share, and reuse safety information more efficiently. However, potential benefits of information sharing are missed due to accident data being inconsistently formatted, non-machine-readable, and inaccessible. Hence, learning opportunities and insights cannot be captured and disseminated to proactively prevent accidents. To address these issues, a novel information sharing system is proposed utilizing linked data, ontologies, and knowledge graph technologies. An ontological approach is developed to semantically model safety information and formalize knowledge pertaining to accident cases. A multi-algorithmic approach is developed for automatically processing and converting accident case data to a resource description framework (RDF), and the SPARQL protocol is deployed to enable query functionalities. Trials and test scenarios utilizing a dataset of 200 real accident cases confirm the effectiveness and efficiency of the system in improving information access, retrieval, and reusability. The proposed development facilitates a new “open” information sharing paradigm with major implications for industry 4.0 and data-driven applications in construction safety management.

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

Cited by 34 publications

References 52 publications

Creating occupant-centered digital twins using the Occupant Feedback Ontology implemented in a smartwatch app

Creating occupant-centered digital twins using the Occupant Feedback Ontology implemented in a smartwatch app

Construction safety ontology development and alignment with industry foundation classes (IFC)

Data-Driven Construction Safety Information Sharing System Based on Linked Data, Ontologies, and Knowledge Graph Technologies

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