Importance of validating an interactive user form
The taxonomy consists of 12 task types grouped into three high-level categories, as shown in table 1: (1) data and view specification (visualize, filter, sort, and derive); (2) view manipulation (select, navigate, coordinate, and organize); and (3) analysis process and provenance (record, annotate, share, and guide).These categories incorporate the critical tasks that enable iterative visual analysis, including visualization creation, interactive querying, multiview coordination, history, and collaboration.By combining a handful of such statements, analysts can construct complex, customized visualizations with a high degree of design control.This approach is used by a number of popular data visualization frameworks such as Leland Wilkinson’s Grammar of Graphics,) provides an example of visualization specification by drag-and-drop operations: analysts place data variables on “shelves” corresponding to visual encodings such as spatial position, size, shape, and color (see figure 1).
To get the most out of such data, however, users must be able to make sense of it: to pursue questions, uncover patterns of interest, and identify (and potentially correct) errors.
Other systems are based on formal grammars for visualization construction.
These grammars constitute high-level languages for succinctly describing how data should be mapped to visual features.
To enable analysts to explore large data sets involving varied data types (e.g., multivariate, geospatial, textual, temporal, networked), flexible visual analysis tools must provide appropriate controls for specifying the data and views of interest.
These controls enable analysts to selectively visualize the data, to filter out unrelated information to focus on relevant items, and to sort information to expose patterns.
Some visualization system designers have explored alternative approaches.