Taking stock: a Linked Data inventory of Compliance Checking terms derived from building regulations

Ruben Krupier; Ioannis  Konstas; Alasdair Gray; Farhad Sadeghineko; Richard Watson; Bimal Kumar

Taking stock: a Linked Data inventory of Compliance Checking terms derived from building regulations

Ruben Krupier^*, Ioannis Konstas, Alasdair Gray, Farhad Sadeghineko, Richard Watson, Bimal Kumar

^*Corresponding author for this work

Architecture and Built Environment Department

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Abstract

Compliance Checking (CC) would be a lot easier if we could automatically map between (1) terms that occur in building regulations and (2) elements of buildings and building products. However, the terminology used in the regulations is vastly different from the terminology found in Building Information Models (BIM). We are therefore forced to somehow shoehorn the vocabulary of regulatory terms into a set of classes that may well be several orders of magnitude smaller. This paper aims to reduce the gap between terms found verbatim in the regulations, and the classes that exist in Linked Data Vocabularies in Architecture and Construction. We explore the automated extraction of domain terminology from building regulations, and interlink the resulting terms with existing controlled vocabularies like Uniclass. The resulting Knowledge Graph (KG) can be used to suggest relevant and related domain terminology, which improves collecting the inventory of Linked Data terms required for CC.

Original language	English
Title of host publication	LDAC 2023
Subtitle of host publication	Linked Data in Architecture and Construction 2023
Place of Publication	Aachen, Germany
Publisher	CEUR
Number of pages	16
Publication status	Published - 15 Jun 2023
Event	11th Linked Data in Architecture and Construction Workshop - Casa delle Tecnologie Emergenti (CTE), Matera, Italy Duration: 15 Jun 2023 → 16 Jun 2023 https://linkedbuildingdata.net/ldac2023/

Publication series

Name	CEUR Workshop Proceedings
Publisher	CEUR
ISSN (Electronic)	1613-0073

Conference

Conference	11th Linked Data in Architecture and Construction Workshop
Abbreviated title	LDAC 2023
Country/Territory	Italy
City	Matera
Period	15/06/23 → 16/06/23
Internet address	https://linkedbuildingdata.net/ldac2023/

Keywords

Automated Compliance Checking
Knowledge Graph
Natural Language Processing
Linked Data

Access to Document

LDAC2023 paper 4692Final published version, 1.79 MBLicence: CC BY

https://linkedbuildingdata.net/ldac2023/abstracts.htmlLicence: CC BY

Cite this

@inproceedings{16597baa91634793b60696ff8b5bc93a,

title = "Taking stock: a Linked Data inventory of Compliance Checking terms derived from building regulations",

abstract = "Compliance Checking (CC) would be a lot easier if we could automatically map between (1) terms that occur in building regulations and (2) elements of buildings and building products. However, the terminology used in the regulations is vastly different from the terminology found in Building Information Models (BIM). We are therefore forced to somehow shoehorn the vocabulary of regulatory terms into a set of classes that may well be several orders of magnitude smaller. This paper aims to reduce the gap between terms found verbatim in the regulations, and the classes that exist in Linked Data Vocabularies in Architecture and Construction. We explore the automated extraction of domain terminology from building regulations, and interlink the resulting terms with existing controlled vocabularies like Uniclass. The resulting Knowledge Graph (KG) can be used to suggest relevant and related domain terminology, which improves collecting the inventory of Linked Data terms required for CC.",

keywords = "Automated Compliance Checking, Knowledge Graph, Natural Language Processing, Linked Data",

author = "Ruben Krupier and Ioannis Konstas and Alasdair Gray and Farhad Sadeghineko and Richard Watson and Bimal Kumar",

year = "2023",

month = jun,

day = "15",

language = "English",

series = "CEUR Workshop Proceedings",

publisher = "CEUR",

booktitle = "LDAC 2023",

note = "11th Linked Data in Architecture and Construction Workshop, LDAC 2023 ; Conference date: 15-06-2023 Through 16-06-2023",

url = "https://linkedbuildingdata.net/ldac2023/",

}

Krupier, R, Konstas, I, Gray, A, Sadeghineko, F, Watson, R & Kumar, B 2023, Taking stock: a Linked Data inventory of Compliance Checking terms derived from building regulations. in LDAC 2023: Linked Data in Architecture and Construction 2023. CEUR Workshop Proceedings, CEUR, Aachen, Germany, 11th Linked Data in Architecture and Construction Workshop, Matera, Italy, 15/06/23. <https://linkedbuildingdata.net/ldac2023/abstracts.html>

Taking stock: a Linked Data inventory of Compliance Checking terms derived from building regulations. / Krupier, Ruben; Konstas, Ioannis ; Gray, Alasdair et al.
LDAC 2023: Linked Data in Architecture and Construction 2023. Aachen, Germany: CEUR, 2023. (CEUR Workshop Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Konstas, Ioannis

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AU - Watson, Richard

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AB - Compliance Checking (CC) would be a lot easier if we could automatically map between (1) terms that occur in building regulations and (2) elements of buildings and building products. However, the terminology used in the regulations is vastly different from the terminology found in Building Information Models (BIM). We are therefore forced to somehow shoehorn the vocabulary of regulatory terms into a set of classes that may well be several orders of magnitude smaller. This paper aims to reduce the gap between terms found verbatim in the regulations, and the classes that exist in Linked Data Vocabularies in Architecture and Construction. We explore the automated extraction of domain terminology from building regulations, and interlink the resulting terms with existing controlled vocabularies like Uniclass. The resulting Knowledge Graph (KG) can be used to suggest relevant and related domain terminology, which improves collecting the inventory of Linked Data terms required for CC.

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