Affiliation:
1. University of Arkansas – Little Rock, USA
Abstract
This chapter focuses on the science of human perception of information quality and describes a subset of Information Quality (IQ) dimensions, which are termed Subjective Information Quality (SIQ). These dimensions typically require a user’s opinion and do not have a clear mathematical technique for finding their value. Note that most dimensions can be measured through multiple techniques, but the SIQ ones are most useful when the user’s experience, opinion, or performance is accounted for. This chapter explores SIQ while considering information obtained from multiple sources, which is a common occurrence when employing visualizations to perform business or intelligence analytics. Thus, the issues addressed here are the assessment of subjective perception of quality of data shown through visual means and principles on how to estimate the subjective quality of combined information sources.
Reference33 articles.
1. The Market for "Lemons": Quality Uncertainty and the Market Mechanism
2. Sample-based quality estimation of query results in relational database environments
3. Threat-related attentional bias in anxious and nonanxious individuals: A meta-analytic study.
4. Bobrowski, M., Marre, M., & Yankelevich, D. (1999). A homogeneous framework to measure data quality. In Proceedings of the 4th International Conference on Information Quality, (pp. 115-124). IEEE.
5. Caballero, I., Verbo, E., Calero, C., & Piattini, M. (2007). A data quality measurement information model based on iso/iec 15939. In Proceedings of the 12th International Conference on Information Quality (pp. 393-408). IEEE.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献