Balzer Christopher, Oktavian Rama, Zandi Mohammad, Fairen-Jimenez David, Moghadam Peyman Z
Department of Chemical and Biological Engineering, University of Sheffield, Sheffield S1 3JD, UK.
Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125, USA.
Patterns (N Y). 2020 Sep 23;1(8):100107. doi: 10.1016/j.patter.2020.100107. eCollection 2020 Nov 13.
In an age of information, visualizing and discerning meaning from data is as important as its collection. Interactive data visualization addresses both fronts by allowing researchers to explore data beyond what static images can offer. Here, we present Wiz, a web-based application for handling and visualizing large amounts of data. Wiz does not require programming or downloadable software for its use and allows scientists and non-scientists to unravel the complexity of data by splitting their relationships through 5D visual analytics, performing multivariate data analysis, such as principal component and linear discriminant analyses, all in vivid, publication-ready figures. With the explosion of high-throughput practices for materials discovery, information streaming capabilities, and the emphasis on industrial digitalization and artificial intelligence, we expect Wiz to serve as an invaluable tool to have a broad impact in our world of big data.
在信息时代,从数据中可视化并识别其意义与数据收集同样重要。交互式数据可视化通过让研究人员能够探索静态图像之外的数据,解决了这两方面的问题。在此,我们展示了Wiz,这是一个用于处理和可视化大量数据的基于网络的应用程序。Wiz使用时不需要编程或下载软件,它允许科学家和非科学家通过5D视觉分析来剖析数据关系的复杂性,进行多元数据分析,如主成分分析和线性判别分析,所有这些都能生成生动的、可用于发表的图形。随着材料发现的高通量实践、信息流能力的爆炸式增长以及对工业数字化和人工智能的重视,我们期望Wiz能成为一个具有宝贵价值的工具,在我们的大数据世界中产生广泛影响。