Lee Doris Jung-Lin, Siddiqui Tarique, Karahalios Karrie, Parameswaran Aditya
University of California, Berkeley, Berkeley, California, USA.
University of Illinois at Urbana-Champaign, Urbana and Champaign, Illinois, USA.
Patterns (N Y). 2020 Oct 9;1(7):100126. doi: 10.1016/j.patter.2020.100126.
Exploratory data analysis is a crucial part of data-driven scientific discovery. Yet, the process of discovering insights from visualization can be a manual and painstaking process. This article discusses some of the lessons we learned from working with scientists in designing visual data exploration system, along with design considerations for future tools.
探索性数据分析是数据驱动的科学发现的关键部分。然而，从可视化中发现见解的过程可能是一个手动且艰苦的过程。本文讨论了我们在与科学家合作设计可视化数据探索系统时学到的一些经验教训，以及对未来工具的设计考量。
