Empirically Measuring Soft Knowledge in Visualization
No Thumbnail Available
Date
2017
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association and John Wiley & Sons Ltd.
Abstract
In this paper, we present an empirical study designed to evaluate the hypothesis that humans' soft knowledge can enhance the cost-benefit ratio of a visualization process by reducing the potential distortion. In particular, we focused on the impact of three classes of soft knowledge: (i) knowledge about application contexts, (ii) knowledge about the patterns to be observed (i.e., in relation to visualization task), and (iii) knowledge about statistical measures. We mapped these classes into three control variables, and used real-world time series data to construct stimuli. The results of the study confirmed the positive contribution of each class of knowledge towards the reduction of the potential distortion, while the knowledge about the patterns prevents distortion more effectively than the other two classes.
Description
@article{10.1111:cgf.13169,
journal = {Computer Graphics Forum},
title = {{Empirically Measuring Soft Knowledge in Visualization}},
author = {Kijmongkolchai, Natchaya and Abdul-Rahman, Alfie and Chen, Min},
year = {2017},
publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.13169}
}