Visualization of Multidimensional Data in Nursing Science.
Visualization of Multidimensional Data in Nursing Science.
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DOI：
10.1177/0193945916672448
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发表时间：
2017-01
影响因子：
1.8
通讯作者：
Johnson C
中科院分区：
文献类型：
--
作者：
Docherty SL;Vorderstrasse A;Brandon D;Johnson C
护理科学家长期以来一直对复杂的、依赖于背景的问题感兴趣，这些问题解决了个人和人群层面的健康和疾病挑战。这些关键问题需要多层次的数据(例如，遗传、生理、生物、行为、情感和社会)。数据收集方法的进步导致收集了大量复杂的、多方面的、往往是不可比较的数据。科学可视化是促进理解这些多维数据集的强大方法工具。我们的目的是展示科学可视化作为一种识别多维数据中的关联、模式和趋势的方法的实用性，如两项研究所示。我们描述了可视化分析的简要历史，科学可视化中涉及的过程，以及可视化方法的使用中的机遇和挑战。科学可视化可以在帮助护士科学家理解他们数据中的结构和潜在模式以回答该领域的关键问题方面发挥关键作用。
Nursing scientists have long been interested in complex, context-dependent questions addressing individual- and population-level challenges in health and illness. These critical questions require multilevel data (e.g., genetic, physiologic, biologic, behavioral, affective, and social). Advances in data-gathering methods have resulted in the collection of large sets of complex, multifaceted, and often non-comparable data. Scientific visualization is a powerful methodological tool for facilitating understanding of these multidimensional data sets. Our purpose is to demonstrate the utility of scientific visualization as a method for identifying associations, patterns, and trends in multidimensional data as exemplified in two studies. We describe a brief history of visual analysis, processes involved in scientific visualization, and opportunities and challenges in the use of visualization methods. Scientific visualization can play a crucial role in helping nurse scientists make sense of the structure and underlying patterns in their data to answer vital questions in the field.