Patterns:Smooth Transitions

From InfoVis:Wiki
Jump to navigation Jump to search

Summary

Category

Interaction

Context

The data is represented in such a way that the entire dataset cannot be viewed at one time. However, the user has a mechanism for spatial movement from one part of the dataset to another. Alternatively a large number of data items captured frequently over a period of time are being viewed using animation.

Problem

How to maintain the users context when travelling through the data space.

Forces

  • Need to maintain context in data space.
  • Moving from one part of the dataset to another.
  • Looking for changes in data over time.

Solution

Use smooth animation and motion. This is especially true for temporal data.

Animation or motion is an effective means of representing data that has some temporal aspect. The most important consideration when using this technique is to make the transition from one state to another as smooth as possible. Animation or motion that produces a large change of state distracts the user from the information and may cause important features to be missed. Large jumps from one location in a 3D environment to another may cause the user to become disoriented a smooth transition helps them to maintain their context in the environment. If possible the user should be able to control the rate of change and direction of the animation, this may allow them to rapidly and accurately explore the data.

There are arguments for not using smooth animation or motion. If the task is to monitor data that may change only gradually over long periods of time, then using large discrete time steps may help the user to identify significant changes in the data. This implies that the application of this pattern may be task dependent.

Examples

Note it is difficult to find examples since researchers tend not to describe the rate at which transitions occur.

Related Patterns

References

  1. Brath, R. (1999) Effective Information Visualization : Guidelines and Metrics for 3D Interactive Representations of Business Data. Masters of Computer Science Thesis, Graduate Department of Computer Science, University of Toronto, Canada.

See Also: Wilkins, B., (2003). “MELD: A Pattern Supported Methodology for Visualisation Design”, PhD Dissertation, University of Birmingham, UK.