Coulentianos, M.J. orcid.org/0000-0001-9414-7844, Abbey, D., So, C.T. et al. (1 more author) (2024) An expert view on data and modelling for planning domestic retrofit. Buildings, 14 (4). 887. ISSN 2075-5309
Abstract
The transition to Net Zero rests partly on the widespread adoption of energy-efficient retrofit measures for domestic dwellings. The scale of retrofit efforts is extensive, as up to 80% of the UK’s domestic housing stock for 2050 has already been built. To address the scope, data and models will play a crucial role in informing design decisions and optimising retrofit strategies. While new methods and tools for data and modelling in retrofit continue to be developed, the perspectives of professionals using these tools on their quality remain mainly absent from discussion across academia and practice. This study investigated the experiences and perceptions of data and modelling from professionals working in the planning stages of domestic retrofit, serving as a needs-finding exercise driving retrofit planning. Through semi-structured interviews and qualitative coding, the results highlight a critical trade-off between precision, confidence, and the burden of data collection. These findings underscore the need to balance precision, ease of use, and adaptability in data and modelling retrofit tools. Issues around data availability and wider access to data and modelling results across stakeholders emerged as a missed opportunity.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
Keywords: | domestic retrofit; data; modelling; interviews |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Civil and Structural Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 08 Apr 2024 14:13 |
Last Modified: | 08 Apr 2024 14:13 |
Status: | Published |
Publisher: | MDPI AG |
Refereed: | Yes |
Identification Number: | 10.3390/buildings14040887 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:211272 |