Please use this identifier to cite or link to this item: https://doi.org/10.1088/1742-6596/2600/3/032003
Title: The Building Data Genome Directory – An open, comprehensive data sharing platform for building performance research
Authors: Jin, Xiaoyu
Fu, Chun
Kazmi, Hussain
Balint, Atilla
Canaydin, Ada
Quintana, Matias 
Biljecki, Filip 
Xiao, Fu
Miller, Clayton 
Issue Date: 1-Nov-2023
Publisher: IOP Publishing
Citation: Jin, Xiaoyu, Fu, Chun, Kazmi, Hussain, Balint, Atilla, Canaydin, Ada, Quintana, Matias, Biljecki, Filip, Xiao, Fu, Miller, Clayton (2023-11-01). The Building Data Genome Directory – An open, comprehensive data sharing platform for building performance research. Journal of Physics: Conference Series 2600 (3) : 032003-032003. ScholarBank@NUS Repository. https://doi.org/10.1088/1742-6596/2600/3/032003
Abstract: Abstract The building sector plays a crucial role in the worldwide decarbonization effort, accounting for significant portions of energy consumption and environmental effects. However, the scarcity of open data sources is a continuous challenge for built environment researchers and practitioners. Although several efforts have been made to consolidate existing open datasets, no database currently offers a comprehensive collection of building data types with all subcategories and time granularities (e.g., year, month, and sub-hour). This paper presents the Building Data Genome Directory, an open data-sharing platform serving as a one-stop shop for the data necessary for vital categories of building energy research. The data directory is an online portal (buildingdatadirectory.org/) that allows filtering and discovering valuable datasets. The directory covers meter, building-level, and aggregated community-level data at the spatial scale and year-to-minute level at the temporal scale. The datasets were consolidated from a comprehensive exploration of sources, including governments, research institutes, and online energy dashboards. The results of this effort include the aggregation of 60 datasets pertaining to building energy ontologies, building energy models, building energy and water data, electric vehicle data, weather data, building information data, text-mining-based research data, image data of buildings, fault detection diagnosis data and occupant data. A crowdsourcing mechanism in the platform allows users to submit datasets they suggest for inclusion by filling out an online form. This directory can fuel research and applications on building energy efficiency, which is an essential step toward addressing the world’s energy and environmental challenges.
Source Title: Journal of Physics: Conference Series
URI: https://scholarbank.nus.edu.sg/handle/10635/246291
ISSN: 1742-6588
1742-6596
DOI: 10.1088/1742-6596/2600/3/032003
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