Publications in Scientific Journals:

C. Bors, S. Kriglstein, T. Gschwandtner, S. Miksch, M. Pohl:
"Visual Interactive Creation, Customization, and Analysis of Data Quality Metrics";
Journal of Data and Information Quality, 10 (2018), 1; 3:1 - 3:26.

English abstract:
During data preprocessing, analysts spend a significant part of their time and effort profiling the quality of the data along with cleansing and transforming the data for further analysis. While quality metrics-ranging from general to domain-specific measures-support assessment of the quality of a dataset, there are hardly any approaches to visually support the analyst in customizing and applying such metrics. Yet, visual approaches could facilitate users´ involvement in data quality assessment. We present MetricDoc, an interactive environment for assessing data quality that provides customizable, reusable quality metrics in combination with immediate visual feedback. Moreover, we provide an overview visualization of these quality metrics along with error visualizations that facilitate interactive navigation of the data to determine the causes of quality issues present in the data. In this article, we describe the architecture, design, and evaluation of MetricDoc, which underwent several design cycles, including heuristic evaluation and expert reviews as well as a focus group with data quality, human-computer interaction, and visual analytics experts.

Data profiling, data quality metrics, visual exploration

"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)

Electronic version of the publication:

Related Projects:
Project Head Silvia Miksch:
CVAST: Centre for Visual Analytics Science and Technology (Laura Bassi Centre of Expertise)

Created from the Publication Database of the Vienna University of Technology.