@Article{Luo2019,
author="Luo, Xiaonan
and Yuan, Yuan
and Zhang, Kaiyuan
and Xia, Jiazhi
and Zhou, Zhiguang
and Chang, Liang
and Gu, Tianlong",
title="Enhancing statistical charts: toward better data visualization and analysis",
journal="Journal of Visualization",
year="2019",
month="Aug",
day="01",
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.",
issn="1875-8975",
doi="10.1007/s12650-019-00569-2",
url="https://doi.org/10.1007/s12650-019-00569-2"
}