4 Big Data Visualization Interaction Modes

In big data visual interaction design, there are four typical interaction modes to solve the complexity of data. They are dynamic change view, multi-view association, view content reduction, focus + context.

Change view dynamically

Dynamically change the view: navigation

Dynamically change the view: multi-attribute sorting


Multi-view association

Multi-view refers to dividing the display area into multiple views or layers, which is a way to reduce the complexity of data. It includes small multi-group images that encode multiple data subsets using the same encoding method, and multi-style images (multi-view) that encode the same data set using different encoding methods.

Side by side: easy to compare, but requires more display space

Layer overlay: the number of layers has a larger limit

The overview diagram and the detail diagram use the same coding method to solve the problem that the data volume is too large to display and solve the problem of lost navigation directions.

Small multi-group charts: display multiple data subsets and complete sets in association

Multi-style coordination and association



View content reduction

It has three advantages: reduce the display content, only display the most interesting, and the user actively filters information or aggregates information.


Focus + context (focus + contex)

Embed the detailed information of the selected element, focus, into the overview information graph in the same view, that is, the context (contex).

Its advantages are to reduce the amount of data displayed in the view through complex filtering and aggregation operations; to alleviate the problem of direction loss caused by standard navigation technology; to provide contextual identification to support positioning.