Interactive visual analytics tool for multidimensional quantitative and categorical data analysis. (July 2020)

• Record Type: Journal Article
• Authors: Shahid, Muhammad Laiq Ur Rahman; Molchanov, Vladimir; Mir, Junaid; Shaukat, Furqan; Linsen, Lars
• Is Part Of: Information visualization. Volume 19:Number 3(2020)
• Page Start: 234
• Page End: 246
• Publication Date: 2020-07
• Subjects: Visual analytics -- multidimensional feature space -- epidemiology -- quantitative and categorical variables; Information visualization -- Periodicals; 006.605
• DOI: 10.1177/1473871620908034
• Languages: English
• ISSNs: 1473-8716

Abstract

With the advances in science and technology, a rapid growth of multidimensional (multivariate) datasets is observed in different fields. Projection and visualization of such data to a lower dimensional space without losing the data structure is a challenging task. We propose an interactive visual analytics tool that is applied for the combined analysis of multidimensional numerical and categorical data. The tool helps the analyst not only to find the clusters of similar objects but also to identify the important features specific to these clusters. The efficacy of the various functionalities of the tool is examined analyzing epidemiological data to understand the pathogenesis of obstructive sleep apnea. Our approach helps the user to visually analyze the data and get a better understanding of the data. The tool would be a valuable resource for analysts working on numerical and categorical data.