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

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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.
Original languageEnglish
Title of host publicationAdvances in Informatics and Computing in Civil and Construction Engineering : Proceedings of the 35th CIB W78 2018 Conference: IT in Design, Construction, and Management
EditorsIvan Mutis, Timo Hartmann
PublisherSpringer Publishing Company
Publication date2019
Pages19-26
Chapter3
ISBN (Print)978-3-030-00220-6
DOIs
Publication statusE-pub ahead of print - 2019
Event35th CIB W78 2018 Conference : IT in Design, Construction, and Management - Chicago, Illinois, United States
Duration: 1 Oct 20183 Oct 2018
Conference number: 35

Conference

Conference35th CIB W78 2018 Conference : IT in Design, Construction, and Management
Number35
CountryUnited States
CityChicago, Illinois
Period01/10/201803/10/2018

Fingerprint

Data mining
Data structures
Semantics
Association rules
Sensors
Ecodesign

Keywords

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

Cite this

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. In I. Mutis, & T. Hartmann (Eds.), Advances in Informatics and Computing in Civil and Construction Engineering: Proceedings of the 35th CIB W78 2018 Conference: IT in Design, Construction, and Management (pp. 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. editor / Ivan Mutis ; Timo Hartmann. Springer Publishing Company, 2019. pp. 19-26
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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.",
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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. in I Mutis & T Hartmann (eds), 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, pp. 19-26, 35th CIB W78 2018 Conference : IT in Design, Construction, and Management, Chicago, Illinois, United States, 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. ed. / Ivan Mutis; Timo Hartmann. Springer Publishing Company, 2019. p. 19-26.

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

TY - GEN

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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

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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. In Mutis I, Hartmann T, editors, 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. p. 19-26 https://doi.org/10.1007/978-3-030-00220-6_3