Automating data management and sharing within a large-scale, heterogeneous sensor network, In: Ames, D.P., Quinn, N.W.T., Rizzoli, A.E. (Eds.)
Hydrology researchers are collecting data using in situ sensors at high frequencies, for extended durations, and with spatial distributions that require infrastructure for data storage, management, and sharing. Managing streaming sensor data is challenging, especially in large networks with large numbers of sites and sensors. The availability and utility of these data in addressing scientific questions related to water availability, water quality, and natural disasters relies on effective cyberinfrastructure that facilitates transformation of raw sensor data into usable data products. It also depends on the ability of researchers to share and access the data in useable formats. In this paper we describe tools that have been developed for research groups and sites conducting long term monitoring using in situ sensors. Functionality includes the ability to track equipment, deployments, calibrations, and other events related to monitoring site maintenance and to link this information to the observational data that they are collecting, which is imperative in ensuring the quality of sensor-based data products. We present these tools in the context of a data management and publication workflow case study for the iUTAH (innovative Urban Transitions and Aridregion Hydrosustainability) network of aquatic and terrestrial sensors. The iUTAH monitoring network includes sensors at aquatic and terrestrial sites for real-time monitoring of common meteorological variables, snow accumulation and melt, soil moisture, surface water flow, and surface water quality. We present the overall workflow we have developed and new software tools that we have deployed for both managing the sensor infrastructure and for storing, managing, and sharing the sensor data.
Horsburgh, J. S., A. S. Jones, S. Reeder (2014). Automating data management and sharing within a large-scale, heterogeneous sensor network, In: Ames, D.P., Quinn, N.W.T., Rizzoli, A.E. (Eds.), Proceedings of the 7th International Congress on Environmental Modelling and Software, June 15-19, San Diego, California, USA. ISBN: 978-88-9035-744-2.