Multivariate Cube for Representing Multivariable Data in Visual Analytics

Autor:	Anh Van Thi Tran, Tuyet Anh Thi Nguyen, Hong Thi Nguyen, Luc Tan Vo, Phuoc Vinh Tran
Rok vydání:	2017
Předmět:	Multivariate statistics Visual analytics business.industry Computer science Multivariable calculus computer.software_genre Variable (computer science) Data visualization Computer graphics (images) Data analysis Data mining Cube business computer Parallel coordinates
Zdroj:	Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ISBN: 9783319563565 ICCASA
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::45403907499876d17a4fd71cd7fc000e https://doi.org/10.1007/978-3-319-56357-2_10 Zobrazit plný text záznamu