Research Article
Multivariate Cube for Representing Multivariable Data in Visual Analytics
@INPROCEEDINGS{10.1007/978-3-319-56357-2_10, author={Hong Nguyen and Anh Thi Tran and Tuyet Thi Nguyen and Luc Vo and Phuoc Tran}, title={Multivariate Cube for Representing Multivariable Data in Visual Analytics}, proceedings={Context-Aware Systems and Applications. 5th International Conference, ICCASA 2016, Thu Dau Mot, Vietnam, November 24-25, 2016, Proceedings}, proceedings_a={ICCASA}, year={2017}, month={6}, keywords={Visual analytics Multivariate cube Multivariable data Data visualization}, doi={10.1007/978-3-319-56357-2_10} }- Hong Nguyen
Anh Thi Tran
Tuyet Thi Nguyen
Luc Vo
Phuoc Tran
Year: 2017
Multivariate Cube for Representing Multivariable Data in Visual Analytics
ICCASA
Springer
DOI: 10.1007/978-3-319-56357-2_10
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.