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Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
10:58

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Published on: January 2, 2011

Evaluation of filesystem provenance visualization tools.

Michelle A Borkin1, Chelsea S Yeh, Madelaine Boyd

  • 1Harvard University.

IEEE Transactions on Visualization and Computer Graphics
|September 21, 2013
PubMed
Summary
This summary is machine-generated.

InProv, a new visualization tool, improves filesystem provenance data exploration accuracy. Its radial layout and time-based node grouping enhance understanding and reduce user effort compared to traditional methods.

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Area of Science:

  • Computer Science
  • Information Visualization
  • Human-Computer Interaction

Background:

  • Filesystem provenance data visualization is crucial for understanding complex hierarchies.
  • Node-link diagrams, common for provenance, lack high-level summaries.
  • Existing tools struggle with large, complex datasets.

Purpose of the Study:

  • Introduce InProv, a novel tool for filesystem provenance visualization.
  • Evaluate InProv against conventional tools (Orbiter) and node grouping methods.
  • Assess user performance, accuracy, and subjective experience.

Main Methods:

  • Developed InProv with an interactive radial tree layout and time-based hierarchical node grouping.
  • Conducted a quantitative user study comparing InProv and Orbiter.
  • Included domain experts, IT professionals, and computational scientists as participants.

Main Results:

  • InProv demonstrated higher accuracy in identifying system activity on large datasets compared to Orbiter.
  • The time-based hierarchical node grouping improved performance and usability in both tools.
  • Participants reported InProv required less mental and physical effort, and was less stressful.

Conclusions:

  • InProv offers a more effective visualization for filesystem provenance data.
  • Time-based hierarchical node grouping significantly enhances data exploration.
  • The study highlights potential gender differences in visualization tool performance.