In the past few years, Geo-spatial data quality has received increasing attention and concerns. As more and more business decisions are made based on data analytic result from geo-spatial related data, low quality data means wrong or inappropriate decisions, which could have substantial effects on a business’s future. In this paper, we propose a framework that can systematically ensure and improve geo-spatial data quality throughout the whole life cycle of data.
CITATION STYLE
Du, X., & Song, W. (2015). Quality improvement framework for business oriented Geo-spatial data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9051, pp. 239–249). Springer Verlag. https://doi.org/10.1007/978-3-319-20370-6_19
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