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User-centered visual explorer of in-process comparison in spatiotemporal space.

Dong Yu1, Oppermann Ian1, Liang Jie1

  • 1School of Computer Science, University of Technology Sydney, Ultimo, Australia.

Journal of Visualization
|November 21, 2022
PubMed
Summary

We developed a user-centered visual explorer (UcVE) for comparing spatiotemporal data. UcVE simplifies complex data exploration with unique visualizations and tracking features.

Keywords:
COVID-19Comparative visualizationProgressive explorationSpatiotemporal featuresUser-centered

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Area of Science:

  • Data Visualization
  • Human-Computer Interaction
  • Geospatial Analysis

Background:

  • Analyzing complex spatiotemporal data requires effective visualization tools.
  • Existing methods often struggle with concurrent comparison of multiple data units.
  • Cognitive load can be a significant barrier in data exploration.

Purpose of the Study:

  • To introduce a user-centered visual explorer (UcVE) for progressive comparison of multiple visualization units in spatiotemporal data.
  • To enhance user cognition by providing tools for visualizing, saving, and tracking exploration results.
  • To facilitate concurrent comparison of historical and current exploration data.

Main Methods:

  • Developed a unique unit visualization employing a flower burst metaphor with customizable aggregated views.
  • Encoded visualization units with abstractions of spatiotemporal properties.
  • Integrated storage sequence and block tracking views for efficient data management.
  • Implemented a flexible geo-based layout with aggregation functions and temporal event timelines.

Main Results:

  • UcVE enables concurrent comparison of multiple visualization units, reducing cognitive load.
  • The system supports flexible exploration through geo-based layouts and temporal views.
  • Demonstrated usefulness with COVID-19 datasets, case studies, and expert feedback.

Conclusions:

  • UcVE offers an effective approach for user-centered spatiotemporal data exploration and comparison.
  • The system's design facilitates efficient analysis of complex datasets.
  • The flower burst visualization metaphor and integrated tracking enhance user exploration capabilities.