An ontology-based framework for building material performance assessment

J.K. Kaltenegger; Kirstine  Meyer Frandsen; Ekaterina Petrova; Pieter Pauwels

doi:10.59490/mg.112

Samenvatting

This study introduces an ontology-based framework leveraging Semantic Web technologies (Berners-Lee et al., 2001) and Linked Data (Bizer et al., 2009) to support MIM for BPS and BIM. The framework relies on Ontology Engineering to represent the domain knowledge related to building material performance (i.e., hygric and thermal material performance). Systems Engineering, coupled with test-driven development, navigates through requirement engineering, semantic data modelling, system definitions, implementation, and validationprocesses. The main contributions of this work encompass a user-friendly web-based application (BIM-MAT) that delivers FAIR material property data to end users during the building design phase.

Originele taal-2	Engels
Pagina's	35
Aantal pagina's	38
DOI's	https://doi.org/10.59490/mg.112
Status	Gepubliceerd - aug. 2024
Evenement	Digitalisation of the Built Environment: 3rd 4TU-14UAS Research Day - Delft, Nederland Duur: 25 apr. 2024 → … Congresnummer: 3

Congres

Congres	Digitalisation of the Built Environment
Land/Regio	Nederland
Stad	Delft
Periode	25/04/24 → …

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10.59490/mg.112

Integrating symbolic and subsymbolic AI for multimodal data fusion and enrichment of Building Digital Twins with material performance data
Petrova, E. (Project Manager), Pauwels, P. (Projectmedewerker) & Kaltenlegger, J. K. (Projectmedewerker)
1/01/24 → 31/12/27
Project: First tier

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title = "An ontology-based framework for building material performance assessment",

abstract = "This study introduces an ontology-based framework leveraging Semantic Web technologies (Berners-Lee et al., 2001) and Linked Data (Bizer et al., 2009) to support MIM for BPS and BIM. The framework relies on Ontology Engineering to represent the domain knowledge related to building material performance (i.e., hygric and thermal material performance). Systems Engineering, coupled with test-driven development, navigates through requirement engineering, semantic data modelling, system definitions, implementation, and validationprocesses. The main contributions of this work encompass a user-friendly web-based application (BIM-MAT) that delivers FAIR material property data to end users during the building design phase.",

keywords = "Artificial Intelligence, Ontology Engineering, Web development",

author = "J.K. Kaltenegger and {Meyer Frandsen}, Kirstine and Ekaterina Petrova and Pieter Pauwels",

year = "2024",

month = aug,

doi = "10.59490/mg.112",

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T1 - An ontology-based framework for building material performance assessment

AU - Kaltenegger, J.K.

AU - Meyer Frandsen, Kirstine

AU - Petrova, Ekaterina

AU - Pauwels, Pieter

N1 - Conference code: 3

PY - 2024/8

Y1 - 2024/8

N2 - This study introduces an ontology-based framework leveraging Semantic Web technologies (Berners-Lee et al., 2001) and Linked Data (Bizer et al., 2009) to support MIM for BPS and BIM. The framework relies on Ontology Engineering to represent the domain knowledge related to building material performance (i.e., hygric and thermal material performance). Systems Engineering, coupled with test-driven development, navigates through requirement engineering, semantic data modelling, system definitions, implementation, and validationprocesses. The main contributions of this work encompass a user-friendly web-based application (BIM-MAT) that delivers FAIR material property data to end users during the building design phase.

AB - This study introduces an ontology-based framework leveraging Semantic Web technologies (Berners-Lee et al., 2001) and Linked Data (Bizer et al., 2009) to support MIM for BPS and BIM. The framework relies on Ontology Engineering to represent the domain knowledge related to building material performance (i.e., hygric and thermal material performance). Systems Engineering, coupled with test-driven development, navigates through requirement engineering, semantic data modelling, system definitions, implementation, and validationprocesses. The main contributions of this work encompass a user-friendly web-based application (BIM-MAT) that delivers FAIR material property data to end users during the building design phase.

KW - Artificial Intelligence

KW - Ontology Engineering

KW - Web development

U2 - 10.59490/mg.112

DO - 10.59490/mg.112

M3 - Abstract

SP - 35

T2 - Digitalisation of the Built Environment

Y2 - 25 April 2024

ER -

An ontology-based framework for building material performance assessment

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Integrating symbolic and subsymbolic AI for multimodal data fusion and enrichment of Building Digital Twins with material performance data

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