IEEE Trans Vis Comput Graph. 2021 Feb;27(2):1860-1870. doi: 10.1109/TVCG.2020.3030340. Epub 2021 Jan 28.
Data science is a rapidly growing discipline and organizations increasingly depend on data science work. Yet the ambiguity around data science, what it is, and who data scientists are can make it difficult for visualization researchers to identify impactful research trajectories. We have conducted a retrospective analysis of data science work and workers as described within the data visualization, human computer interaction, and data science literature. From this analysis we synthesis a comprehensive model that describes data science work and breakdown to data scientists into nine distinct roles. We summarise and reflect on the role that visualization has throughout data science work and the varied needs of data scientists themselves for tooling support. Our findings are intended to arm visualization researchers with a more concrete framing of data science with the hope that it will help them surface innovative opportunities for impacting data science work. Data availability: https://osf.io/z2xpd/?view_only=87fa24be486a473884adb9ffbe8db4ec.
数据科学是一个快速发展的学科，组织越来越依赖数据科学工作。然而，数据科学的模糊性，它是什么，以及数据科学家是谁，使得可视化研究人员难以确定有影响力的研究轨迹。我们对数据可视化、人机交互和数据科学文献中描述的数据科学工作和工作者进行了回顾性分析。通过这项分析，我们综合了一个全面的模型，描述了数据科学工作，并将数据科学家细分为九个不同的角色。我们总结并反思了可视化在数据科学工作中的作用，以及数据科学家自身对工具支持的不同需求。我们的研究结果旨在为可视化研究人员提供一个更具体的数据科学框架，希望这将帮助他们发现影响数据科学工作的创新机会。数据可用性：https://osf.io/z2xpd/?view_only=87fa24be486a473884adb9ffbe8db4ec。
