A taxonomy of quality assessment methods for volunteered and crowdsourced geographic information
A new article from the partnership between AGORA Research Group and GIScience Research Group was accepted for publishing in the Transactions in GIS Journal. In this article, it was proposed a taxonomy of methods for assessing the quality of CGI when no reference data are available, which is likely to be the most common situation in practice. The taxonomy includes 11 quality assessment methods that were identified by means of a systematic literature review. These methods are described in detail, including their main characteristics and limitations. This taxonomy not only provides a systematic and comprehensive account of the existing set of methods for CGI quality assessment, but also enables researchers working on the quality of CGI in various sources (e.g., social media, crowd sensing, collaborative mapping) to learn from each other, thus opening up avenues for future work that combines and extends existing methods into new application areas and domains. The open access version of the article can be accessed here.
How to cite this article: Degrossi LC, Albuquerque JP, Rocha RS, Zipf A. A taxonomy of quality assessment methods for volunteered and crowdsourced geographic information. Transactions in GIS. 2018;22:542–560. https://doi.org/10.1111/tgis.12329