Outlier detection methods to improve the quality of citizen science data

International Journal of Biometeorology
Jennifer S LiElisabeth Beaubien

Abstract

Citizen science involves public participation in research, usually through volunteer observation and reporting. Data collected by citizen scientists are a valuable resource in many fields of research that require long-term observations at large geographic scales. However, such data may be perceived as less accurate than those collected by trained professionals. Here, we analyze the quality of data from a plant phenology network, which tracks biological response to climate change. We apply five algorithms designed to detect outlier observations or inconsistent observers. These methods rely on different quantitative approaches, including residuals of linear models, correlations among observers, deviations from multivariate clusters, and percentile-based outlier removal. We evaluated these methods by comparing the resulting cleaned datasets in terms of time series means, spatial data coverage, and spatial autocorrelations after outlier removal. Spatial autocorrelations were used to determine the efficacy of outlier removal, as they are expected to increase if outliers and inconsistent observations are successfully removed. All data cleaning methods resulted in better Moran's I autocorrelation statistics, with percentile-based outl...Continue Reading

References

Sep 19, 2000·International Journal of Biometeorology·E G Beaubien, H J Freeland
Jan 22, 2004·Bioinformatics·Emmanuel ParadisKorbinian Strimmer
Jan 28, 2004·Nucleic Acids Research·Pawel GajerSteven L Salzberg
Jul 10, 2009·Trends in Ecology & Evolution·Jonathan Silvertown
Jun 21, 2011·International Journal of Biometeorology·Elisabeth G Beaubien, Andreas Hamann
Sep 3, 2013·International Journal of Biometeorology·Mark D SchwartzLiang Liang
Sep 3, 2014·International Journal of Biometeorology·Kerissa K FuccilloTimothy S Elder
Dec 24, 2014·Biodiversity Data Journal·Cherian MathewCarole Goble
May 21, 2017·International Journal of Biometeorology·Alison Donnelly, Rong Yu
May 8, 2018·International Journal of Biometeorology·Richard E FeldmanAbraham J Miller-Rushing

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