Data Quality: Detection and Management of Outliers

  • Ferdinando UrbanoEmail author
  • Mathieu Basille
  • Francesca Cagnacci


Tracking data can potentially be affected by a large set of errors in different steps of data acquisition and processing. Erroneous data can heavily affect analysis, leading to biased inference and misleading wildlife management/conservation suggestions. Data quality assessment is therefore a key step in data management. In this chapter, we especially deal with biased locations, or ‘outliers’. While in some cases incorrect data are evident, in many situations, it is not possible to clearly identify locations as outliers because although they are suspicious (e.g. long distances covered by animals in a short time or repeated extreme values), they might still be correct, leaving a margin of uncertainty. In this chapter, different potential errors are identified and a general approach to managing outliers is proposed that tags records rather than deleting them. According to this approach, practical methods to find and mark errors are illustrated on the database created in  Chaps. 2,  3,  4,  5,  6 and  7.


Outlier detection GPS accuracy Animal movement Erroneous data 


  1. Bjorneraas K, van Moorter B, Rolandsen CM, Herfindal I (2010) Screening GPS location data for errors using animal movement characteristics. J Wild Manage 74:1361–1366. doi: 10.1111/j.1937-2817.2010.tb01258.x CrossRefGoogle Scholar
  2. Frair JL, Fieberg J, Hebblewhite M, Cagnacci F, DeCesare NJ, Pedrotti L (2010) Resolving issues of imprecise and habitat-biased locations in ecological analyses using GPS telemetry data. Philos Trans R Soc B 365:2187–2200. doi: 10.1098/rstb.2010.0084 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Ferdinando Urbano
    • 1
    Email author
  • Mathieu Basille
    • 2
  • Francesca Cagnacci
    • 3
  1. 1.Università Iuav di VeneziaVeniceItaly
  2. 2.Fort Lauderdale Research and Education CenterUniversity of FloridaFort LauderdaleUSA
  3. 3.Biodiversity and Molecular Ecology Department, Research and Innovation CentreFondazione Edmund MachS.Michele all’Adige, TNItaly

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