A scalable, interactive widget library for visualizing biological data

In addition to the overall size of the data set, what makes large time-varying data visualization hard is the need to constantly transfer each time step of the data from disk to

In this paper we studied the tempo- ral coherence of sequential times and histogram and spatial distribution of data in time-varying data sets and proposed a new data structure

The table view extends the known table lens as follows: We cluster related elements to reduce subsampling artifacts and achieve table size independent rendering time; we

We experimented with two different visualization techniques to make the data accessible: A thumbnail view which takes newspapers as entities (Figure 2) and a bubble view that puts

The star-coordinates widget can be used for interactive analysis of multidimensional data: When the user changes the position of a certain axis of the widget, the column of

In a scatterplot view (top right) we link the structures of the time series data (position information) and of the attribute space (similarity-preserving color

Figure 1: Conventional volume rendering shows time-dependent data as animation, which can convey qualitative temporal development well but does not provide an overview of the whole

Three different view configurations (shared view, split screen, and split screen with navigation information) for multi-user collaboration with a wall-size display were introduced