The author proposes a taxonomy of tasks for seven different types of data:1-D,2-D,3 - D,temporal, multidimensional, tree and network. Each of these data types are explained in detail. The author considers the 'Overview first, zoom and filter, then details-on-demand' principle to be the most important guideline in information visualization.
The basic tasks for each of the seven different data types along with examples are identified. Some of the tasks can be termed as follows: Overview, zoom, filter,details-on-demand, relate,history,extract. The author also discusses about dynamic filtering which will help the users answer specific questions about the dataset. Some of the approaches for specifying the queries using Boolean expressions are discussed.
Most of the concepts are explained in detail but there are some terms like the starfield displays, perspective wall etc which have little or no explanation. The readers have to refer additional papers to understand better.
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