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An Open Data Science Approach for Building Performance Studies

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Conference Proceeding by ASHRAE, 2018

Category:

Description

Open Science is increasingly viewed as a priority for collaboration and advancement of scientific disciplines. This paper presents two Open Science methods for building performance studies: i) a method for storing building performance information using an open data format, including the creation of a custom XML schema and the novel use of both XML and CSV formats for data storage; and ii) a method for carrying out building performance analysis in an open and reproducible manner using the Jupyter Notebook tool.The work is based on the open-access REFIT Smart Home dataset (publically available at https://doi.org/10.17028/rd.lboro.2070091.v1), a published dataset of building performance information in 20 UK homes. The dataset includes detailed building survey information and over 1.3 billion sensor readings.The paper concludes with a discussion on the future of Open Science approaches for building performance studies, and how the processes described in the paper can be applied to both measurement and simulation datasets.

Citation: ASHRAE/IBPSA-USA Bldg Simulation Conf, Sept 2018

Product Details

Published:
2018
Number of Pages:
8
Units of Measure:
Dual
File Size:
1 file , 5 MB
Product Code(s):
D-BSC18-C097