Challenges in Building an End-to-End System for Acquisition, Management, and Integration of Diverse Data From Sensor Networks in Watersheds: Lessons From a Mountainous Community Observatory in East River, Colorado
Author
Varadharajan, CharulekaFaybishenko, Boris
Henderson, Amanda
Henderson, Matthew
Hendrix, Valerie C.
Hubbard, Susan S.
Kakalia, Zarine
Newman, Alexander
Potter, Benjamin
Steltzer, Heidi
Versteeg, Roelof
Agarwal, Deborah A.
Williams, Kenneth H.
Wilmer, Chelsea
Wu, Yuxin
Brown, Wendy
Burrus, Madison
Carroll, Rosemary W. H.
Christianson, Danielle S.
Dafflon, Baptiste
Dwivedi, Dipankar
Enquist, Brian J.
Affiliation
Univ Arizona, Dept Ecol & Evolutionary BiolIssue Date
2019-12-05Keywords
RiversData models
Monitoring
Temperature measurement
Data collection
Snow
Biology
Sensor systems and applications
sensors
geoscience
water resources
watershed
data management
data integration
data processing
co-design
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Varadharajan, C., Faybishenko, B., Henderson, A., Henderson, M., Hendrix, V. C., Hubbard, S. S., … Enquist, B. J. (2019). Challenges in Building an End-to-End System for Acquisition, Management, and Integration of Diverse Data From Sensor Networks in Watersheds: Lessons From a Mountainous Community Observatory in East River, Colorado. IEEE Access, 7, 182796–182813. https://doi.org/10.1109/access.2019.2957793 Journal
IEEE ACCESSRights
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
The U.S. Department of Energy's Watershed Function Scientific Focus Area (SFA), centered in the East River, Colorado, generates diverse datasets including hydrological, geological, geochemical, geophysical, ecological, microbiological and remote sensing data. The project has deployed extensive field infrastructure involving hundreds of sensors that measure highly diverse phenomena (e.g. stream and groundwater hydrology, water quality, soil moisture, weather) across the watershed. Data from the sensor network are telemetered and automatically ingested into a queryable database. The data are subsequently quality checked, integrated with the United States Geological Survey's stream monitoring network using a custom data integration broker, and published to a portal with interactive visualizations. The resulting data products are used in a variety of scientific modeling and analytical efforts. This paper describes the SFA's end-to-end infrastructure and services that support the generation of integrated datasets from a watershed sensor network. The development and maintenance of this infrastructure, presents a suite of challenges from practical field logistics to complex data processing, which are addressed through various solutions. In particular, the SFA adopts a holistic view for data collection, assessment and integration, which dramatically improves the products generated, and enables a co-design approach wherein data collection is informed by model results and vice-versa.Note
Open access journalISSN
2169-3536Version
Final published versionSponsors
U.S. Department of EnergyUnited States Department of Energy (DOE) [DE-AC02-05CH11231]; WatershedFunction Scientific Focus Area - U.S. Department of Energy, Office of Science, Office of Biological, and Environmental ResearchUnited States Department of Energy (DOE) [DE-AC02-05CH11231]; National Energy Research Scientific Computing Center (NERSC), U.S. Department of Energy Office of Science User FacilityUnited States Department of Energy (DOE) [DE-AC02-05CH11231]; Environmental Systems Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) [DE-AC02-05CH11231]; [DE-SC0009732]; [DE-SC0018447]ae974a485f413a2113503eed53cd6c53
10.1109/access.2019.2957793
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Except where otherwise noted, this item's license is described as This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/.