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    Author(s): John L. CampbellLindsey E. Rustad; John H. Porter; Jeffrey R. Taylor; Ethan W. Dereszynski; James B. Shanley; Corinna Gries; Donald L. Henshaw; Mary E. Martin; Wade. M. Sheldon; Emery R. Boose
    Date: 2013
    Source: BioScience. 63(7): 574-585
    Publication Series: Scientific Journal (JRNL)
    Station: Northern Research Station
    PDF: View PDF  (803.44 KB)

    Description

    Sensor networks are revolutionizing environmental monitoring by producing massive quantities of data that are being made publically available in near real time. These data streams pose a challenge for ecologists because traditional approaches to quality assurance and quality control are no longer practical when confronted with the size of these data sets and the demands of real-time processing. Automated methods for rapidly identifying and (ideally) correcting problematic data are essential. However, advances in sensor hardware have outpaced those in software, creating a need for tools to implement automated quality assurance and quality control procedures, produce graphical and statistical summaries for review, and track the provenance of the data. Use of automated tools would enhance data integrity and reliability and would reduce delays in releasing data products. Development of community-wide standards for quality assurance and quality control would instill confidence in sensor data and would improve interoperability across environmental sensor networks.

    Publication Notes

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    Citation

    Campbell, John L.; Rustad, Lindsey E.; Porter, John H.; Taylor, Jeffrey R.; Dereszynski, Ethan W.; Shanley, James B.; Gries, Corinna; Henshaw, Donald L.; Martin, Mary E.; Sheldon, Wade. M.; Boose, Emery R. 2013. Quantity is nothing without quality: automated QA/QC for streaming sensor networks. BioScience. 63(7): 574-585.

    Keywords

    computers in biology, informatics, instrumentation, environmental science

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