Supporting data and tools for "Impact of data temporal resolution on quantifying residential end uses of water"
| Authors: | |
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| Owners: | Camilo J. Bastidas PachecoJeffery S. Horsburgh |
| Type: | Resource |
| Storage: | The size of this resource is 16.1 MB |
| Created: | Apr 19, 2022 at 5:10 p.m. |
| Last updated: | Aug 08, 2022 at 4:47 p.m. (Metadata update) |
| Published date: | Aug 08, 2022 at 4:46 p.m. |
| DOI: | 10.4211/hs.6625bdbde41c45c2b906f32be7ea70f0 |
| Citation: | See how to cite this resource |
| Sharing Status: | Published |
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| Views: | 1517 |
| Downloads: | 63 |
| +1 Votes: | Be the first one to this. |
| Comments: | No comments (yet) |
Abstract
The files provided here are the supporting data and code files for the analyses presented in "Impact of data temporal resolution on quantifying residential end uses of water", an article submitted to the Water journal (https://www.mdpi.com/journal/water) The journal paper assessed how the temporal resolution at which water use data are collected impacts our ability to identify water end use events, calculate features of individual events, and classify events by end use. Additionally, we also explored implications for data management associated with collecting this type of data as well as methods and tools for analyzing and extracting information from it. The data were collected in the cities of Logan and Providence, Utah, USA in 2022 and are included in this resource. The code and data included in this resource allow replication of the analyses presented in the journal paper, and the raw data included allow for extension of the analyses conducted.
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Related Resources
| The content of this resource references | GitHub repository for the pulse datalogger used to collect the data in this study: https://github.com/UCHIC/CIWS-Pulse-Logger |
| This resource is referenced by | Bastidas Pacheco, C.J., Horsburgh, J.S.., Beckwith, A.J. (2022). Impact of temporal resolution on data for quantifying residential end uses of water. Submitted for publication in the Water journal. |
Credits
Funding Agencies
This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number |
|---|---|---|
| National Science Foundation | Cyberinfrastructure for Intelligent Water Supply (CIWS): Shrinking Big Data for Sustainable Urban Water | 1552444 |
| Utah Water Research Laboratory |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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