Abstract
Visualization of multivariate data is a big challenge to problems of visual analytics. A system of data visualization is composed of visual mapping stage and visual display stage. The stage of visual mapping converts data to graph and the stage of visual display shows the graph on screen in accordance with human’s retinal perception which is specified by visual features and Gestalt’s laws. Based on data characteristics, multidimensional cubes representing multivariate data are classified as non-spatial multidimensional cube for non-spatial data, spatial multidimensional cube for spatio-temporal data, spatio-temporal multidimensional cube for movement data, and 3D-spatio-temporal multidimensional cube for flight data. For a visualization system responding human’s retinal perception, multidimensional cubes have to enable analysts to answer elementary questions concerning individual values, variation questions concerning part of data or overall data, and relation questions resulting in the correlation among attributes.
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Thi Nguyen, H., Thi Pham, T.M., Thi Nguyen, T.A., Thi Tran, A.V., Vinh Tran, P., Van Pham, D. (2019). Two-Stage Approach to Classifying Multidimensional Cubes for Visualization of Multivariate Data. In: Cong Vinh, P., Alagar, V. (eds) Context-Aware Systems and Applications, and Nature of Computation and Communication. ICCASA ICTCC 2018 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 266. Springer, Cham. https://doi.org/10.1007/978-3-030-06152-4_7
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