June 26, 2018
A new study focused on Quality Control (QC) methodology in the iUTAH project using GAMUT data. Researchers Amber Jones, Jeff Horsburgh, and Dave Eiriksson published an article titled “Assessing subjectivity in environmental sensor data post processing via a controlled experiment” in the July 2018 edition of Ecological Informatics. The article used high frequency environmental data collected by sensors in GAMUT or 'Gradients Along Mountain to Urban Transitions,’ iUTAH’s ecohydrologic observatory, to examine QC procedures to observe and review post-processing results.
In this paper, researchers were able to compare QC post processing of sensor data by multiple participants, including whether experienced participants' results were more variable than novices. They then looked at participants' data shifts at calibration events that caused the greatest discrepancies. Finally, the paper made recommendations include prescriptive procedures and collaborative quality control.
Results suggest that to “improve consistency, clarifying QC guidelines and protocols and thoroughly training technicians is recommended. Implementing a collaborative QC process is also suggested wherein the changes introduced by QC for sensitive periods are reviewed for cases where highly accurate data are required. Because of the resources demanded by review and collaboration, in determining QC workflows, scientists should look to balance the level of review with the potential improvements in processed data quality and precision.”
The article can be viewed under the title “Assessing subjectivity in environmental sensor data post processing via a controlled experiment.”
Jones, A.S., J.S. Horsburgh, and D. Eiriksson. 2018. Assessing subjectivity in environmental sensor data post processing via a controlled experiment. Ecological Informatics, 36: 86-86. 10.1016/j.ecoinf.2018.05.001.
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