Abstract
Decision-makers often rely on data to support their decision-making processes. There is strong evidence, however, that data quality problems are widespread in practice and that reliance on data of poor or uncertain quality leads to less-effective decision-making. Addressing this issue requires first a means of understanding data quality and then techniques both for improving data quality and for improving decision-making based on data quality information. This paper presents a semiotic-based framework for understanding data quality that consists of three categories: syntactic (form), semantic (meaning) and pragmatic (use). This framework is then used as a basis for discussing data quality problems, improvement, and tags, where tags are used to provide data quality information to decisionmakers.
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Price, R., Shanks, G. (2008). Data Quality and Decision Making. In: Handbook on Decision Support Systems 1. International Handbooks Information System. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-48713-5_4
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DOI: https://doi.org/10.1007/978-3-540-48713-5_4
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