Rodenbeck Eric
Stamen Design, 2017 Mission Street No. 300, San Francisco, CA 94110, USA.
Integr Comp Biol. 2018 Dec 1;58(6):1247-1254. doi: 10.1093/icb/icy105.
Science, in the popular imagination, is about finding answers to questions. Scientists make discoveries, develop theories, and deliver those discoveries and theories to audiences with an interest in the truth as backed up by science. Well-designed data visualization (dataviz), by contrast, can generate and address not only new questions but new kinds of questions. It has the particular quality of allowing its viewers, users, and makers the ability to generate new inquiries, and to put them in a better place to answer them. Dataviz offers esthetic and interactive platforms for discussion and inquiry that can help scientists to both do their work and better communicate their work to broader audiences. Here I will illustrate and examine case studies from multiple points along the rich and varied possibility space that opens up when science and dataviz work together. I will also introduce three communication principles that I have learned from my involvement with hundreds of dataviz projects over the years. Well-designed dataviz can help scientists and those involved with science find ways to navigate the multiple competing interests and priorities inherent in both communication to non-scientists and exploratory data-rich interfaces.
在大众的想象中，科学就是寻找问题的答案。科学家进行发现、发展理论，并将这些发现和理论传递给对科学所支持的真理感兴趣的受众。相比之下，精心设计的数据可视化（dataviz）不仅可以产生并解决新问题，还能产生新类型的问题。它具有一种特殊的特质，能让其观众、用户和制作者有能力提出新的疑问，并使他们更有能力回答这些疑问。数据可视化提供了美观且交互式的讨论和探究平台，有助于科学家开展工作，并更好地向更广泛的受众传达他们的工作成果。在此，我将举例说明并审视一些案例研究，这些案例来自科学与数据可视化协同工作时所展现出的丰富多样的可能性空间中的多个角度。我还将介绍我在多年参与数百个数据可视化项目过程中学到的三条沟通原则。精心设计的数据可视化可以帮助科学家以及与科学相关的人员找到方法，以应对在与非科学家沟通以及探索富含数据的界面时所固有的多种相互竞争的利益和优先事项。
