Representing Data Quality

Abstract

Information on data quality is important for effective use of GIS data. It impacts the credibility of data representation and the confidence that is attached to data interpretations. It impacts the reliability of interpretations and thus decision making based on GIS modeling and data exploration. A number of impediments to representing data quality can be cited, including impediments to definition and assessment, to attribution in a database, and to graphical depiction. This paper elaborates on impediments to representing data quality. The discussion provides a window through which the complexity of representing data quality may be viewed, and to introduce current research efforts and avenues for further research addressing each impediment.