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Using Visual Exploratory Data Analysis to Facilitate Collaboration and Hypothesis Generation in Cross-Disciplinary Research

机译:在跨学科研究中使用视觉探索性数据分析促进协作和假设的产生

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Massive open data resources are changing the way that people do science. To make use of those data resources, data science methods and technology can be leveraged by stakeholders of various disciplines. The objective of this paper is to present our experience of using visual exploratory data analysis as a method to facilitate collaboration and hypothesis generation in geoscience research. The research team consisted of both geoscientists and computer scientists. A use case-driven, iterative approach was applied to create a collaborative and communicative environment. Through several rounds of use case analysis and technological development, a data visualization pilot system was created for studying the co-relationships between chemical elements and mineral species. The exploratory data analyses conducted in those use case studies led to several research hypotheses for future work. This research illustrates the usefulness of exploratory data analysis for hypothesis generation in a data science process. Although the presented project is in geoscience, the discussed method and experience can also be translated into other disciplines.
机译:大量的开放数据资源正在改变人们进行科学的方式。为了利用这些数据资源,各个学科的利益相关者可以利用数据科学方法和技术。本文的目的是介绍我们使用视觉探索性数据分析作为在地球科学研究中促进协作和假设生成的方法的经验。研究团队由地球科学家和计算机科学家组成。应用了用例驱动的迭代方法来创建协作和交流的环境。通过几轮用例分析和技术开发,创建了一个数据可视化试验系统,用于研究化学元素与矿物种类之间的相互关系。在这些用例研究中进行的探索性数据分析得出了一些未来工作的研究假设。这项研究说明了探索性数据分析对于数据科学过程中的假设生成的有用性。尽管提出的项目涉及地球科学,但是讨论的方法和经验也可以转化为其他学科。

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