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Cyberinfrasructure for Intelligent Water Supply Data Visualization Challenge

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Cyberinfrastructure for Intelligent Water Supply (CIWS) Data Visualization Challenge

This repository contains results of the Visualization challenge events sponsored by the NSF funded Cyberinfrastructure for Intelligent Water Supply project. To date, two editions of the challenges have been held. For details and results, including the winning entries, visit the links below.

The Challenge

Our research group is developing cyberinfrastructure to better support the collection, management, and use of smart water metering data. This Challenge has provided students at Utah State University with an opportunity to develop potentially novel and innovative visualizations of high resolution residential water use data. We aim to develop new approaches for providing visual feedback directly to residential water users about their own water use.

Given high temporal resolution residential water use data this challenge focuses on development of visualizations that would be useful in communicating the timing, volume, and distribution of water use within the home. For example, what useful information could be extracted from the data and presented to the homeowner that might influence their water use behavior?

Visualizations devloped for this challenge have been focused on creating visual information that would be useful for residential water users to inform them about thier own water consumption. Thus, the objective has been to create visualizations that are easily understandable and that may provide actionable information (e.g., the homeowner can see thier water use visually and may change their behavoir based on the information you provide).

Visit the Documentation Pages

Access Information About our Research Group's Project Here

We have developed a set of documentation pages that provide background about our research project along with links to supporting literature.

Access Additional Documentation

Contacts

  • For information about the Visualization Challenge, the challenge dataset, or if you have general questions, contact Jeff Horsburgh at jeff.horsburgh@usu.edu

Sponsors and Credits

NSF-1552444

The material in this repository is based on work supported by National Science Foundation Grant CBET 1552444. Any opinions, findings, and conclusions or recommendations expressed are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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