Abstract
After a first phase of almost unanimous enthusiasm, VGI research identified data quality as a major problem of community-based data acquisition. This is especially true in the scenario studied in this article: the integration of geo-tagged reports about events or incidents. Missing and conflicting values appear frequently, due to the non-professional and subjective character of such data. We discuss data quality issues in this emerging subarea of VGI and present a computational approach for handling incomplete and inconsistent data based on constraint satisfaction techniques. The method is evaluated on a dataset of reports about vegetation periods of plants. It turns out that even simple pieces of the otherwise very complex contextual information can be used to increase the quality of VGI.
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We would like to thank the BudBurstproject team for making their data publicly available and for providing us with great support.
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Yanenko, O., Schlieder, C. (2012). Enhancing the Quality of Volunteered Geographic Information: A Constraint-Based Approach. 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_23
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DOI: https://doi.org/10.1007/978-3-642-29063-3_23
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