Analyzing of Evaluation Indices Based on Analytical Experience via Data Quality Visualization

Abstract

In recent years, the development of the data distribution market has led to active data transactions between different companies and organizations. When trading data, ensuring the quality of data meets the request of purchasers is essential. However, the need for standard indices for assessing the data quality has resulted in variability in quality evaluations of individuals' background knowledge, skills, or experiences. In this paper, we proposed the "quality metadata," which is the automated visualization for supporting the evaluation of the data quality by inputting the actual datasets. The experimental findings indicated that evaluators' tendencies in assessing data quality varied based on their data analysis experience and their use of quality metadata by different evaluation indices.