Midway Stephen R
Department of Oceanography and Coastal Sciences, Louisiana State University, Baton Rouge, LA 70803, USA.
Patterns (N Y). 2020 Nov 11;1(9):100141. doi: 10.1016/j.patter.2020.100141. eCollection 2020 Dec 11.
We live in a contemporary society surrounded by visuals, which, along with software options and electronic distribution, has created an increased importance on effective scientific visuals. Unfortunately, across scientific disciplines, many figures incorrectly present information or, when not incorrect, still use suboptimal data visualization practices. Presented here are ten principles that serve as guidance for authors who seek to improve their visual message. Some principles are less technical, such as determining the message before starting the visual, while other principles are more technical, such as how different color combinations imply different information. Because figure making is often not formally taught and figure standards are not readily enforced in science, it is incumbent upon scientists to be aware of best practices in order to most effectively tell the story of their data.
我们生活在一个被视觉元素包围的当代社会，这些视觉元素连同软件选项和电子传播方式，使得有效的科学视觉呈现变得愈发重要。不幸的是，在各个科学学科中，许多图表都错误地呈现信息，或者即便信息无误，仍采用次优的数据可视化方法。本文提出了十条原则，为那些希望提升其视觉传达效果的作者提供指导。有些原则技术性较低，比如在开始制作视觉呈现之前确定要传达的信息，而其他原则技术性更强，比如不同的颜色组合如何暗示不同的信息。由于科学领域中图表制作往往未得到正式教授，图表标准也未得到切实执行，科学家有责任了解最佳实践方法，以便最有效地讲述他们的数据故事。
