OLIVE: Multi-D



Multi-dimensional information visualizations present data that is not primarily spatial. The number of attributes of a given item in the collection is more than three. Example applications of multi-dimensional visualization schemes may use stock market statistics, factory production line data sets, a set of books in a library, a movie database, and almost any abstract and statistical information about any phenomenon.

Attributes in multi-dimensional visualizations should have approximately equal weights. One, two, three dimensional, and temporal information visualization schemes can be viewed as a subset of multi-dimensional information visualization. There is an implicit domination of some of the attributes in these types of visualizations. For example, time is the inherent attribute in a temporal visualization scheme. Hence, we believe that one, two, three dimensional, and temporal visualization schemes should be classified separately from multi-dimensional visualization. Also, attributes in multi-dimensional visualizations should have no explicit structure or relations between them. For example, data sets that lead to an immediate hierarchy or a network structure should also have their own categories.

Scientific visualization also deals with multi-dimensional data but most of the data sets used in this field use the spatial attributes of the data for visualization purposes. For example, Computer-Aided Tomography Systems, Computer-Aided Design Systems, and many of the Geographical Information Systems use either the Cartesian coordinate system or the geographical coordinates of the data to achieve a reasonable visualization of the data. Hence, we believe that scientific visualization should be analyzed in a separate category. On the other hand, we believe that some of the combinations of multi-dimensional visualization approaches and scientific visualization schemes can still be considered as multi-dimensional visualization applications.






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