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Related Experiment Video

Updated: Jun 19, 2026

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Published on: February 9, 2017

Temporal summaries: supporting temporal categorical searching, aggregation and comparison.

Taowei David Wang¹, Catherine Plaisant, Ben Shneiderman

¹Human-Computer Interaction Lab and Department of Computer Science, University of Maryland at College Park, USA. tw7@cs.umd.edu

IEEE Transactions on Visualization and Computer Graphics

|October 17, 2009

Summary

Temporal summaries are an interactive visualization tool that aggregates event data across multiple granularities. This technique helps analysts spot trends, compare groups, and filter data for insights in event histories.

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Area of Science:

Information Visualization
Data Analysis
Human-Computer Interaction

Background:

Analyzing large event histories requires tools that emphasize event prevalence and temporal order.
Previous work introduced align, rank, and filter (ARF) for temporal ordering.
Flexible comparison capabilities are crucial for visual evidence gathering.

Purpose of the Study:

Introduce temporal summaries, an interactive visualization technique.
Highlight event occurrence prevalence and temporal dynamics.
Support trend spotting and group comparison in event data.

Main Methods:

Developed temporal summaries for dynamic aggregation of events.
Implemented multi-granularity aggregation (year, month, week, day, hour).
Integrated temporal range filtering affordances for interactive analysis.

Main Results:

Demonstrated applicability in two extensive case studies.
Analysts successfully used temporal summaries for searching, filtering, and pattern discovery.
Validated the technique with electronic health records and academic records.

Conclusions:

Temporal summaries effectively highlight event prevalence and temporal ordering.
The technique supports flexible comparisons and trend analysis.
Interactive visualization aids analysts in uncovering insights from complex event histories.