Visualization of Multidimensional Data in Nursing Science

Sharron L. Docherty, Allison Vorderstrasse, Debra Brandon, Constance Johnson

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)112-126
Number of pages15
JournalWestern Journal of Nursing Research
Volume39
Issue number1
DOIs
StatePublished - Jan 1 2017

Keywords

  • Big Data
  • data analysis
  • data integration
  • data science
  • multidimensional data
  • visualization

ASJC Scopus subject areas

  • Nursing(all)

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