Introductory overview: Recommendations for approaching scientific visualization with large environmental datasets

Christa Kelleher, Anna Braswell

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


Scientific visualizations are the foundation for communicating results and findings to a variety of audiences. As the creation of novel and large environmental datasets has grown, this has necessitated new schemes and recommendations for creating effective visualizations. In this overview, we review the foundations of scientific visualization and considerations for visualization of large datasets within the context of the four Vs of big data (volume, variety, veracity, and velocity). Using big datasets requires making decisions as to whether to aggregate or preserve details, approaches for grouping to enable comparisons, and considering how best to show complex data in many-dimensional space. To enable more effective visualizations, we provide several considerations regarding common decisions faced during the visualization process. These recommendations are accompanied by examples applied to existing large datasets. While our recommendations are just that, they encourage intentionality and awareness of the choices faced when visualizing scientific datasets.

Original languageEnglish (US)
Article number105113
JournalEnvironmental Modelling and Software
StatePublished - Sep 2021


  • Graphics
  • Multidimensional
  • Plots
  • Scientific visualization
  • Visual analytics
  • Visual communication

ASJC Scopus subject areas

  • Software
  • Environmental Engineering
  • Ecological Modeling


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