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Understanding Open Access Data Using Visuals: Integrating Prospective Studies of Children's Responses to Natural

Hazel J Shah1, Betty S Lai2, Audrey J Leroux3

  • 1Centers for Disease Control and Prevention, 1600 Clifton Road NE, C-09, Atlanta, GA 30333, USA.

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Summary

Visuals help researchers understand complex open access data, identify patterns, and integrate information from multiple studies. Developing data visualization skills is crucial for researchers navigating the growing landscape of open data.

Keywords:
HurricaneIntegrated datasetsNatural disasterOpen access dataPatternsVisuals

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Area of Science:

  • Psychology
  • Data Science
  • Research Methodology

Background:

  • Increasing access to open data enables powerful statistical analyses.
  • Researchers face challenges in understanding and utilizing open access datasets.
  • Visualizations are key to overcoming these challenges and enhancing data comprehension.

Purpose of the Study:

  • Illustrate how visuals address researcher challenges with open access data.
  • Demonstrate methods for familiarizing with new datasets.
  • Showcase techniques for identifying patterns and integrating multi-study data.

Main Methods:

  • Utilized data from an integrative data analysis of children's responses to four hurricanes.
  • Assessed hurricane exposure, posttraumatic stress, anxiety, social support, and life events.
  • Included 1707 participants (53.61% female), aged 7–16 years.

Main Results:

  • Visuals effectively aid in understanding new and unfamiliar datasets.
  • Data visualization facilitates the identification of patterns and trends.
  • Visual tools support the integration of information from diverse sources.

Conclusions:

  • Researchers need enhanced data visualization skills for open access data.
  • Graduate programs should increase programming and data visualization training.
  • Current academic and publishing practices impact data visualization.