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Related Experiment Video

Updated: Apr 12, 2026

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
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A data management and publication workflow for a large-scale, heterogeneous sensor network.

Amber Spackman Jones1, Jeffery S Horsburgh, Stephanie L Reeder

  • 1Utah Water Research Laboratory, Utah State University, 8200 Old Main Hill, Logan, UT, 84322-8200, USA, amber.jones@usu.edu.

Environmental Monitoring and Assessment
|May 14, 2015
PubMed
Summary

Researchers developed open-source tools and a workflow for managing high-volume sensor data in hydrology. This system transforms raw data into usable products, improving water availability and disaster research.

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Area of Science:

  • Environmental Science
  • Hydrology
  • Data Science

Background:

  • High-frequency, long-duration in situ sensor data in hydrology generate large volumes requiring robust infrastructure.
  • Effective cyberinfrastructure is crucial for transforming raw sensor data into usable products for water availability, quality, and natural disaster research.
  • Data accessibility and usability are key for scientific advancement in hydrological studies.

Purpose of the Study:

  • To describe a data management and publication workflow for long-term in situ sensor monitoring.
  • To introduce software tools designed for research groups and sites collecting extensive sensor data.
  • To present a case study of these tools within the innovative Urban Transitions and Aridregion Hydrosustainability (iUTAH) sensor network.

Main Methods:

  • Development of a data management and publication workflow.
  • Implementation of software tools for tracking equipment inventory and field maintenance events.
  • Integration of equipment information with observational data to ensure data quality.
  • Deployment of open-source tools for data storage, management, and sharing.

Main Results:

  • A comprehensive workflow for transferring field monitoring data to end-users was established.
  • Software tools were deployed for efficient storage, management, and sharing of sensor data.
  • The system successfully managed data from the iUTAH sensor network, monitoring various environmental variables.

Conclusions:

  • The developed workflow and open-source tools effectively address the challenges of managing large-scale sensor data in hydrology.
  • Linking equipment and maintenance data to observational data enhances the quality of sensor-based products.
  • The presented solutions are transferable and available for use by other research groups.