Why Interactive Data Visualization?
Static visualizations can offer only precomposed views of data, so multiple static views are often needed to present a variety of perspectives on the same information. It is important to remember that well-designed static visualizations can work well in presentations, but they are not well suited for exploring large amounts of new, unknown data. Traditional diagrams are simply static drawings that cannot show relationships or structures in understandable ways. In addition, the number of dimensions of data are limited and when all visual elements must be present on the same surface at the same time. Representing multidimensional datasets fairly in static images becomes very complex.
Dynamic, interactive visualizations can empower people to explore the data for themselves. The basic functions of most interactive visualization tools have changed little since 1996, when Ben Shneiderman of the University of Maryland first proposed a "Visual Information Seeking Mantra": overview first, zoom and filter, then details-on-demand.
Protovis: A Graphical Toolkit for Visualization
Protovis was originally developed at Stanford, and is no longer under active development. The Protovis team is now developing a new visualization library, D3.js, with improved support for animation and interaction. D3 builds on many of the concepts in Protovis; for more details, please read the introduction and browse the examples.
The original SIMILE project, started in 2003 and concluded in 2011, was jointly conducted by the MIT Libraries and MIT CSAIL. SIMILE Widges consists of four widgets, which are Exhibit, Timeline, Timeplot and Runway. These widgets are free, open source data visualization web widgets.