Abstract
This paper presents a platform, called QualESTIM, for exploring socioeconomic statistical data (also called indicators). QualESTIM integrates various outlier detection methods that make it possible to evaluate the logical consistency of a dataset, and its quality in fine. Without recourse to ‘ground truth’ of some kind, data values are compared to various spatiotemporal distributions given by statistical models. However, an outlier is not necessarily an error: experts should always interpret the outlying value. That is why we claim here that such a quality assessment process has to be interactive and that metadata associated with such data should be made available in order to refine the analysis. Dedicated to outlier detection and their visualization by an expert, the platform is connected to a database that contains both the data and their metadata, structured according to an ISO 19115 profile. A case study illustrates the interest of this approach.
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Acknowledgements
The research presented in this paper has been supported by the ESPON 2013 database project, of the European Spatial Planning and Observation Network for Territorial Cohesion. We would like to thank Claude Grasland for its advices, as well as Martin Charlton and Paul Harris who provided the implementation of the outlier detection methods in R. The authors would like to thank the reviewers for their comments that help to improve the paper.
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Plumejeaud, C., Villanova-Oliver, M. (2012). QualESTIM: Interactive Quality Assessment of Socioeconomic Data Using Outlier Detection. In: Gensel, J., Josselin, D., Vandenbroucke, D. (eds) Bridging the Geographic Information Sciences. Lecture Notes in Geoinformation and Cartography(). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29063-3_8
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DOI: https://doi.org/10.1007/978-3-642-29063-3_8
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