@article{ref1,
title="Enhancing statistical charts: toward better data visualization and analysis",
journal="Journal of visualization (Tokyo)",
year="2019",
author="Luo, Xiaonan and Yuan, Yuan and Zhang, Kaiyuan and Xia, Jiazhi and Zhou, Zhiguang and Chang, Liang and Gu, Tianlong",
volume="22",
number="4",
pages="819-832",
abstract="Conventional statistical charts are widely used in visual analysis. With the development of digital techniques, statistical charts are confronted with problems when data grow in scale and complexity. Accordingly, a huge amount of effort has been paid on the enhancement of standard charts, making the design space dramatically increased. It is cumbersome for naive users to choose appropriate design in a specific analysis scenario. In this paper, we survey the enhancement techniques for a compact set of statistical charts, and identify the types and usage scenarios. Motivated by the new problems, such as data volume and complexity, we present a challenge-and-task-driven framework to guide the understanding of the design space and the decision-making process.Graphic abstract Open image in new window<p /> <p>Language: en</p>",
language="en",
issn="1343-8875",
doi="10.1007/s12650-019-00569-2",
url="http://dx.doi.org/10.1007/s12650-019-00569-2"
}