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2017 | OriginalPaper | Buchkapitel

Multivariate Cube for Representing Multivariable Data in Visual Analytics

verfasst von : Hong Thi Nguyen, Anh Van Thi Tran, Tuyet Anh Thi Nguyen, Luc Tan Vo, Phuoc Vinh Tran

Erschienen in: Context-Aware Systems and Applications

Verlag: Springer International Publishing

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Abstract

The data visualization enables users to contribute their knowledge and experience to the analysis of data stored in storages or resulted from collecting systems in real time. Visual techniques displaying data table as 2D or 3D charts, pies, lines, and so on, do not completely enable to explore multivariable data. Multivariate cube is modified from parallel coordinates by rotating the reference axis to the direction perpendicular to parallel coordinates plane. Multivariate cube represents multivariable data to enable users to answer elementary tasks in visual analytics by associating a point with its references on axes of 3-dimensional coordinates. Multivariate cube represents visually multivariable data to enable users to answer synoptic tasks in visual analytics by viewing the variation of data along the reference axis for each variable, or viewing the correlation between variables on the plane being perpendicular to and moving along the reference axis. Multivariate cube is illustrated in this paper with two case studies for visual analytics, the evaluation of learning outcomes of a program of higher education and the happenings of a disease.

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Metadaten
Titel
Multivariate Cube for Representing Multivariable Data in Visual Analytics
verfasst von
Hong Thi Nguyen
Anh Van Thi Tran
Tuyet Anh Thi Nguyen
Luc Tan Vo
Phuoc Vinh Tran
Copyright-Jahr
2017
DOI
https://doi.org/10.1007/978-3-319-56357-2_10

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