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Devillers, R., Stein, A., Bédard, Y., Chrisman, N., Fisher, P. and Shi, W. (2010) Thirty Years of Research on Spatial Data Quality: Achievements, Failures, and Opportunities. Transactions in GIS, 14, 387-400.
https://doi.org/10.1111/j.1467-9671.2010.01212.x

has been cited by the following article:

• TITLE: On Statistical Measures for Data Quality Evaluation

  AUTHORS: Xiaoxia Han

  KEYWORDS: GIS Data Quality, Sensitivity, Specificity, Kappa, Weighted Kappa, Bland-Altman Analysis, Intra-Class Correlation Coefficient

  JOURNAL NAME: Journal of Geographic Information System, Vol.12 No.3, June 11, 2020

  ABSTRACT: Most GIS databases contain data errors. The quality of the data sources such as traditional paper maps or more recent remote sensing data determines spatial data quality. In the past several decades, different statistical measures have been developed to evaluate data quality for different types of data, such as nominal categorical data, ordinal categorical data and numerical data. Although these methods were originally proposed for medical research or psychological research, they have been widely used to evaluate spatial data quality. In this paper, we first review statistical methods for evaluating data quality, discuss under what conditions we should use them and how to interpret the results, followed by a brief discussion of statistical software and packages that can be used to compute these data quality measures.