In Search of Sustainable Design Patterns: Combining Data Mining and Semantic Data Modelling on Disparate Building Data

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

Resumé

Cross-domain analytical techniques have made the prediction of outcomes in building design more accurate. Yet, many decisions are based on rules of thumb and previous experiences, and not on documented evidence. That results in inaccurate predictions and a difference between predicted and actual building performance. This article aims to reduce the occurrence of such errors using a combination of data mining and semantic modelling techniques, by deploying these technologies in a use case, for which sensor data is collected. The results present a semantic building data graph enriched with discovered motifs and association rules in observed properties. We conclude that the combination of semantic modelling and data mining techniques can contribute to creating a repository of building data for design decision support.
OriginalsprogEngelsk
TitelAdvances in Informatics and Computing in Civil and Construction Engineering : Proceedings of the 35th CIB W78 2018 Conference: IT in Design, Construction, and Management
RedaktørerIvan Mutis, Timo Hartmann
ForlagSpringer Publishing Company
Publikationsdato2019
Sider19-26
Kapitel3
ISBN (Trykt)978-3-030-00220-6
DOI
StatusE-pub ahead of print - 2019
Begivenhed35th CIB W78 2018 Conference : IT in Design, Construction, and Management - Chicago, Illinois, USA
Varighed: 1 okt. 20183 okt. 2018
Konferencens nummer: 35

Konference

Konference35th CIB W78 2018 Conference : IT in Design, Construction, and Management
Nummer35
LandUSA
ByChicago, Illinois
Periode01/10/201803/10/2018

Fingeraftryk

Data mining
Data structures
Semantics
Association rules
Sensors
Ecodesign

Emneord

  • BIM
  • Semantics
  • Data mining
  • Pattern recognition
  • Knowledge discovery

Citer dette

Petrova, E. A., Pauwels, P., Svidt, K., & Jensen, R. L. (2019). In Search of Sustainable Design Patterns: Combining Data Mining and Semantic Data Modelling on Disparate Building Data. I I. Mutis, & T. Hartmann (red.), Advances in Informatics and Computing in Civil and Construction Engineering: Proceedings of the 35th CIB W78 2018 Conference: IT in Design, Construction, and Management (s. 19-26). Springer Publishing Company. https://doi.org/10.1007/978-3-030-00220-6_3
Petrova, Ekaterina Aleksandrova ; Pauwels, Pieter ; Svidt, Kjeld ; Jensen, Rasmus Lund. / In Search of Sustainable Design Patterns : Combining Data Mining and Semantic Data Modelling on Disparate Building Data. Advances in Informatics and Computing in Civil and Construction Engineering: Proceedings of the 35th CIB W78 2018 Conference: IT in Design, Construction, and Management. red. / Ivan Mutis ; Timo Hartmann. Springer Publishing Company, 2019. s. 19-26
@inproceedings{6b1309e2552a48e1ae4005631a12b24d,
title = "In Search of Sustainable Design Patterns: Combining Data Mining and Semantic Data Modelling on Disparate Building Data",
abstract = "Cross-domain analytical techniques have made the prediction of outcomes in building design more accurate. Yet, many decisions are based on rules of thumb and previous experiences, and not on documented evidence. That results in inaccurate predictions and a difference between predicted and actual building performance. This article aims to reduce the occurrence of such errors using a combination of data mining and semantic modelling techniques, by deploying these technologies in a use case, for which sensor data is collected. The results present a semantic building data graph enriched with discovered motifs and association rules in observed properties. We conclude that the combination of semantic modelling and data mining techniques can contribute to creating a repository of building data for design decision support.",
keywords = "BIM, Semantics, Data mining, Pattern recognition, Knowledge discovery, BIM, Semantics, Data mining, Pattern recognition, Knowledge discovery",
author = "Petrova, {Ekaterina Aleksandrova} and Pieter Pauwels and Kjeld Svidt and Jensen, {Rasmus Lund}",
year = "2019",
doi = "10.1007/978-3-030-00220-6_3",
language = "English",
isbn = "978-3-030-00220-6",
pages = "19--26",
editor = "Ivan Mutis and Timo Hartmann",
booktitle = "Advances in Informatics and Computing in Civil and Construction Engineering",
publisher = "Springer Publishing Company",
address = "United States",

}

Petrova, EA, Pauwels, P, Svidt, K & Jensen, RL 2019, In Search of Sustainable Design Patterns: Combining Data Mining and Semantic Data Modelling on Disparate Building Data. i I Mutis & T Hartmann (red), Advances in Informatics and Computing in Civil and Construction Engineering: Proceedings of the 35th CIB W78 2018 Conference: IT in Design, Construction, and Management. Springer Publishing Company, s. 19-26, Chicago, Illinois, USA, 01/10/2018. https://doi.org/10.1007/978-3-030-00220-6_3

In Search of Sustainable Design Patterns : Combining Data Mining and Semantic Data Modelling on Disparate Building Data. / Petrova, Ekaterina Aleksandrova; Pauwels, Pieter; Svidt, Kjeld; Jensen, Rasmus Lund.

Advances in Informatics and Computing in Civil and Construction Engineering: Proceedings of the 35th CIB W78 2018 Conference: IT in Design, Construction, and Management. red. / Ivan Mutis; Timo Hartmann. Springer Publishing Company, 2019. s. 19-26.

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

TY - GEN

T1 - In Search of Sustainable Design Patterns

T2 - Combining Data Mining and Semantic Data Modelling on Disparate Building Data

AU - Petrova, Ekaterina Aleksandrova

AU - Pauwels, Pieter

AU - Svidt, Kjeld

AU - Jensen, Rasmus Lund

PY - 2019

Y1 - 2019

N2 - Cross-domain analytical techniques have made the prediction of outcomes in building design more accurate. Yet, many decisions are based on rules of thumb and previous experiences, and not on documented evidence. That results in inaccurate predictions and a difference between predicted and actual building performance. This article aims to reduce the occurrence of such errors using a combination of data mining and semantic modelling techniques, by deploying these technologies in a use case, for which sensor data is collected. The results present a semantic building data graph enriched with discovered motifs and association rules in observed properties. We conclude that the combination of semantic modelling and data mining techniques can contribute to creating a repository of building data for design decision support.

AB - Cross-domain analytical techniques have made the prediction of outcomes in building design more accurate. Yet, many decisions are based on rules of thumb and previous experiences, and not on documented evidence. That results in inaccurate predictions and a difference between predicted and actual building performance. This article aims to reduce the occurrence of such errors using a combination of data mining and semantic modelling techniques, by deploying these technologies in a use case, for which sensor data is collected. The results present a semantic building data graph enriched with discovered motifs and association rules in observed properties. We conclude that the combination of semantic modelling and data mining techniques can contribute to creating a repository of building data for design decision support.

KW - BIM

KW - Semantics

KW - Data mining

KW - Pattern recognition

KW - Knowledge discovery

KW - BIM

KW - Semantics

KW - Data mining

KW - Pattern recognition

KW - Knowledge discovery

U2 - 10.1007/978-3-030-00220-6_3

DO - 10.1007/978-3-030-00220-6_3

M3 - Article in proceeding

SN - 978-3-030-00220-6

SP - 19

EP - 26

BT - Advances in Informatics and Computing in Civil and Construction Engineering

A2 - Mutis, Ivan

A2 - Hartmann, Timo

PB - Springer Publishing Company

ER -

Petrova EA, Pauwels P, Svidt K, Jensen RL. In Search of Sustainable Design Patterns: Combining Data Mining and Semantic Data Modelling on Disparate Building Data. I Mutis I, Hartmann T, red., Advances in Informatics and Computing in Civil and Construction Engineering: Proceedings of the 35th CIB W78 2018 Conference: IT in Design, Construction, and Management. Springer Publishing Company. 2019. s. 19-26 https://doi.org/10.1007/978-3-030-00220-6_3