Enhancing the Quality of Volunteered Geographic Information: A Constraint-Based Approach

Chapter
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

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.

Keywords

Constraint Satisfaction Constraint Propagation Constraint Graph Volunteer Geographic Information Binary Constraint 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Notes

Acknowledgments

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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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Chair of Computing in the Cultural SciencesUniversity of BambergBambergGermany

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