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  5. Building performance evaluation using OpenMath and Linked Data
 
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Building performance evaluation using OpenMath and Linked Data

Author(s)
Hu, Shushan  
Corry, Edward  
Horrigan, Matthew  
Hoare, Cathal  
Dos Reis, Mathilde  
O'Donnell, James  
Uri
http://hdl.handle.net/10197/10999
Date Issued
2018-09-01
Date Available
2019-08-20T09:48:55Z
Abstract
A pronounced gap often exists between expected and actual building performance. The multi-faceted and cross lifecycle causes of this performance gap are found in design assumptions, construction issues and commissioning and operational compromises. Some important factors are firmly rooted in the lack of interoperability around building information. New solutions to the interoperability challenge offer the potential to leverage and reuse available heterogeneous data in a manner that can significantly assist building performance assessment. Linked data provides an open, modular and extensible solution for the challenge. However, in the buildings domain, the integration of rule-based performance metrics and contextual information has yet to be formally established. This paper describes an approach to the provision of in-depth building performance assessment through the integration of OpenMath and linked data. An ontology describing performance metrics in RDF is presented, together with an automated metric evaluation solution using multi-silo queries and computer algebra systems, providing a flexible, automated and extensible mechanism for the assessment of building performance. Building managers and engineers can simultaneously analyse time-series building performance at a range of levels, without burdensome manual intervention such as is the case with traditional solutions. A test implementation on a large university building highlights the potential of this solution.
Sponsorship
European Commission - Seventh Framework Programme (FP7)
Type of Material
Journal Article
Publisher
Elsevier
Journal
Energy and Buildings
Volume
174
Start Page
484
End Page
494
Copyright (Published Version)
2018 Elsevier
Subjects

Building performance ...

Data interoperability...

Linked data

OpenMath

Performance metric

DOI
10.1016/j.enbuild.2018.07.007
Language
English
Status of Item
Peer reviewed
ISSN
0378-7788
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
File(s)
No Thumbnail Available
Name

2018_Hu_SemanticWebScenarioModellingOpenMath.pdf

Size

8 MB

Format

Adobe PDF

Checksum (MD5)

fa9bb97f62ffa2c1edc499101a8f77ef

Owning collection
Mechanical & Materials Engineering Research Collection
Mapped collections
Energy Institute Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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