The application of web of data technologies in building materials information modelling for construction waste analytics

Muhammad Bilal; Lukumon O. Oyedele; Kamran Munir; Saheed O. Ajayi; Olugbenga O. Akinade; Hakeem A. Owolabi; Hafiz A. Alaka

doi:10.1016/j.susmat.2016.12.004

The application of web of data technologies in building materials information modelling for construction waste analytics

Muhammad Bilal, Lukumon O. Oyedele, Kamran Munir, Saheed O. Ajayi, Olugbenga O. Akinade, Hakeem A. Owolabi, Hafiz A. Alaka

University of the West of England

Research output: Contribution to journal › Article › peer-review

22 Citations (Scopus)

145 Downloads (Pure)

Abstract

Predicting and designing out construction waste in real time is complex during building waste analysis (BWA) since it involves a large number of analyses for investigating multiple waste-efficient design strategies. These analyses require highly specific data of materials that are scattered across different data sources. A repository that facilitates applications in gaining seamless access to relatively large and distributed data sources of building materials is currently unavailable for conducting the BWA. Such a repository is the first step to developing a simulation tool for the BWA. Existing product data exchange ontologies and classification systems lack adequate modelling of building materials for the BWA. In this paper, we propose a highly resilient and data-agnostic building materials database. We use ontologies at the core of our approach to capture highly accurate and semantically conflicting data of building materials using the Resource Description Framework (RDF) and Web Ontology Language (OWL). Owing to the inherent capabilities of RDF, the architecture provides syntactical homogeneity while accessing the diverse and distributed data of building materials during the BWA. We use software packages such as Protégé and Oracle RDF Graph database for implementing the proposed architecture. Our research provides technical details and insights for researchers and software engineers who are seeking to develop the semantic repositories of similar kind of simulation applications that can be used for building waste performance analysis.

Original language	English
Pages (from-to)	28-37
Number of pages	10
Journal	Sustainable Materials and Technologies
Volume	11
DOIs	https://doi.org/10.1016/j.susmat.2016.12.004
Publication status	Published - 1 Apr 2017
Externally published	Yes

Bibliographical note

NOTICE: this is the author’s version of a work that was accepted for publication in Sustainable Materials and Technologies. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Sustainable Materials and Technologies, [11, (2017)] DOI: 10.1016/j.susmat.2016.12.004

© 2017, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

Keywords

Big data analytics
Building materials database
Building waste analysis
Construction waste minimisation
NoSQL systems
Ontologies
RDF/OWL

ASJC Scopus subject areas

Renewable Energy, Sustainability and the Environment
General Materials Science
Waste Management and Disposal
Industrial and Manufacturing Engineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.susmat.2016.12.004

Post-PrintAccepted author manuscript, 1.08 MBLicence: CC BY-NC-ND

https://uwe-repository.worktribe.com/output/900334/the-application-of-web-of-data-technologies-in-building-materials-information-modelling-for-construction-waste-analyticsLicence: CC BY-NC-ND

Cite this

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title = "The application of web of data technologies in building materials information modelling for construction waste analytics",

abstract = "Predicting and designing out construction waste in real time is complex during building waste analysis (BWA) since it involves a large number of analyses for investigating multiple waste-efficient design strategies. These analyses require highly specific data of materials that are scattered across different data sources. A repository that facilitates applications in gaining seamless access to relatively large and distributed data sources of building materials is currently unavailable for conducting the BWA. Such a repository is the first step to developing a simulation tool for the BWA. Existing product data exchange ontologies and classification systems lack adequate modelling of building materials for the BWA. In this paper, we propose a highly resilient and data-agnostic building materials database. We use ontologies at the core of our approach to capture highly accurate and semantically conflicting data of building materials using the Resource Description Framework (RDF) and Web Ontology Language (OWL). Owing to the inherent capabilities of RDF, the architecture provides syntactical homogeneity while accessing the diverse and distributed data of building materials during the BWA. We use software packages such as Prot{\'e}g{\'e} and Oracle RDF Graph database for implementing the proposed architecture. Our research provides technical details and insights for researchers and software engineers who are seeking to develop the semantic repositories of similar kind of simulation applications that can be used for building waste performance analysis.",

keywords = "Big data analytics, Building materials database, Building waste analysis, Construction waste minimisation, NoSQL systems, Ontologies, RDF/OWL",

author = "Muhammad Bilal and Oyedele, {Lukumon O.} and Kamran Munir and Ajayi, {Saheed O.} and Akinade, {Olugbenga O.} and Owolabi, {Hakeem A.} and Alaka, {Hafiz A.}",

note = "NOTICE: this is the author{\textquoteright}s version of a work that was accepted for publication in Sustainable Materials and Technologies. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Sustainable Materials and Technologies, [11, (2017)] DOI: 10.1016/j.susmat.2016.12.004 {\textcopyright} 2017, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ ",

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doi = "10.1016/j.susmat.2016.12.004",

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journal = "Sustainable Materials and Technologies",

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AU - Bilal, Muhammad

AU - Oyedele, Lukumon O.

AU - Munir, Kamran

AU - Ajayi, Saheed O.

AU - Akinade, Olugbenga O.

AU - Owolabi, Hakeem A.

AU - Alaka, Hafiz A.

N1 - NOTICE: this is the author’s version of a work that was accepted for publication in Sustainable Materials and Technologies. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Sustainable Materials and Technologies, [11, (2017)] DOI: 10.1016/j.susmat.2016.12.004 © 2017, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

PY - 2017/4/1

Y1 - 2017/4/1

N2 - Predicting and designing out construction waste in real time is complex during building waste analysis (BWA) since it involves a large number of analyses for investigating multiple waste-efficient design strategies. These analyses require highly specific data of materials that are scattered across different data sources. A repository that facilitates applications in gaining seamless access to relatively large and distributed data sources of building materials is currently unavailable for conducting the BWA. Such a repository is the first step to developing a simulation tool for the BWA. Existing product data exchange ontologies and classification systems lack adequate modelling of building materials for the BWA. In this paper, we propose a highly resilient and data-agnostic building materials database. We use ontologies at the core of our approach to capture highly accurate and semantically conflicting data of building materials using the Resource Description Framework (RDF) and Web Ontology Language (OWL). Owing to the inherent capabilities of RDF, the architecture provides syntactical homogeneity while accessing the diverse and distributed data of building materials during the BWA. We use software packages such as Protégé and Oracle RDF Graph database for implementing the proposed architecture. Our research provides technical details and insights for researchers and software engineers who are seeking to develop the semantic repositories of similar kind of simulation applications that can be used for building waste performance analysis.

AB - Predicting and designing out construction waste in real time is complex during building waste analysis (BWA) since it involves a large number of analyses for investigating multiple waste-efficient design strategies. These analyses require highly specific data of materials that are scattered across different data sources. A repository that facilitates applications in gaining seamless access to relatively large and distributed data sources of building materials is currently unavailable for conducting the BWA. Such a repository is the first step to developing a simulation tool for the BWA. Existing product data exchange ontologies and classification systems lack adequate modelling of building materials for the BWA. In this paper, we propose a highly resilient and data-agnostic building materials database. We use ontologies at the core of our approach to capture highly accurate and semantically conflicting data of building materials using the Resource Description Framework (RDF) and Web Ontology Language (OWL). Owing to the inherent capabilities of RDF, the architecture provides syntactical homogeneity while accessing the diverse and distributed data of building materials during the BWA. We use software packages such as Protégé and Oracle RDF Graph database for implementing the proposed architecture. Our research provides technical details and insights for researchers and software engineers who are seeking to develop the semantic repositories of similar kind of simulation applications that can be used for building waste performance analysis.

KW - Big data analytics

KW - Building materials database

KW - Building waste analysis

KW - Construction waste minimisation

KW - NoSQL systems

KW - Ontologies

KW - RDF/OWL

U2 - 10.1016/j.susmat.2016.12.004

DO - 10.1016/j.susmat.2016.12.004

M3 - Article

AN - SCOPUS:85009067789

SN - 2214-9937

VL - 11

SP - 28

EP - 37

JO - Sustainable Materials and Technologies

JF - Sustainable Materials and Technologies

ER -

The application of web of data technologies in building materials information modelling for construction waste analytics

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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Cite this