A Global Building Occupant Behavior Database.
Authors
Dong, Bing
Mu, Wei
Jiang, Zixin
Pandey, Pratik
Olesen, Bjarne
Lawrence, Thomas
O'Neil, Zheng
Andrews, Clinton
Bandurski, Karol
Bavaresco, Mateus
Berger, Christiane
Burry, Jane
Erba, Silvia
Gao, Nan
Graham, Lindsay T
Grassi, Camila
Jain, Rishee
Li, Zhengrong
Mahdavi, Ardeshir
Malik, Jeetika
Marschall, Max
Neves, Leticia
O'Brien, William
Pan, Song
Park, June Young
Pigliautile, Ilaria
Piselli, Cristina
Pisello, Anna Laura
Rafsanjani, Hamed Nabizadeh
Salim, Flora
Sonta, Andrew
Touchie, Marianne
Wagner, Andreas
Walsh, Sinead
Wang, Zhe
Webber, David M
Zangheri, Paolo
Zhang, Jingsi
Zhou, Xiang
Zhou, Xin
Publication Date
2022-06-28Journal Title
Sci Data
ISSN
2052-4463
Publisher
Springer Science and Business Media LLC
Volume
9
Issue
1
Language
en
Type
Article
This Version
VoR
Metadata
Show full item recordCitation
Dong, B., Liu, Y., Mu, W., Jiang, Z., Pandey, P., Hong, T., Olesen, B., et al. (2022). A Global Building Occupant Behavior Database.. Sci Data, 9 (1) https://doi.org/10.1038/s41597-022-01475-3
Abstract
This paper introduces a database of 34 field-measured building occupant behavior datasets collected from 15 countries and 39 institutions across 10 climatic zones covering various building types in both commercial and residential sectors. This is a comprehensive global database about building occupant behavior. The database includes occupancy patterns (i.e., presence and people count) and occupant behaviors (i.e., interactions with devices, equipment, and technical systems in buildings). Brick schema models were developed to represent sensor and room metadata information. The database is publicly available, and a website was created for the public to access, query, and download specific datasets or the whole database interactively. The database can help to advance the knowledge and understanding of realistic occupancy patterns and human-building interactions with building systems (e.g., light switching, set-point changes on thermostats, fans on/off, etc.) and envelopes (e.g., window opening/closing). With these more realistic inputs of occupants' schedules and their interactions with buildings and systems, building designers, energy modelers, and consultants can improve the accuracy of building energy simulation and building load forecasting.
Keywords
Data Descriptor, /706/4066/4065, /706/689/680, data-descriptor
Sponsorship
American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) (1883-RP)
Identifiers
s41597-022-01475-3, 1475
External DOI: https://doi.org/10.1038/s41597-022-01475-3
This record's URL: https://www.repository.cam.ac.uk/handle/1810/338595
Rights
Licence:
http://creativecommons.org/licenses/by/4.0/
Statistics
Total file downloads (since January 2020). For more information on metrics see the
IRUS guide.
Recommended or similar items
The current recommendation prototype on the Apollo Repository will be turned off on 03 February 2023. Although the pilot has been fruitful for both parties, the service provider IKVA is focusing on horizon scanning products and so the recommender service can no longer be supported. We recognise the importance of recommender services in supporting research discovery and are evaluating offerings from other service providers. If you would like to offer feedback on this decision please contact us on: support@repository.cam.ac.uk