Visualization of Multidimensional Data in Nursing Science

Abstract

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.

Keywords: Big Data; data analysis; data integration; data science; multidimensional data; visualization.

Figure 1

Case browser overview. (The color version of this figure is available in the online version at http://wjn.sagepub.com/supplemental.)

Figure 2

Co-occurrence of key events and provider perceptions of hope and discomfort.

Figure 3

Dashboard of multiple visualizations.