Visual Analytics: A Comprehensive Overview

Abstract

With the ever-increasing amount of data, the world has stepped into the era of ''Big Data''. Presently, the analysis of massive and complex data and the extraction of relevant information, have been become essential tasks in many fields of studies, such as health, biology, chemistry, social science, astronomy, and physics. However, compared with the development of data storage and management technologies, our ability to gain useful information from the collected data does not match our ability to collect the data. This gap has led to a surge of research activity in the field of visual analytics. Visual analytics employs interactive visualization to integrate human judgment into algorithmic data-analysis processes. In this paper, the aim is to draw a complete picture of visual analytics to direct future research by examining the related research in various application domains. As such, a novel categorization of visual-analytics applications from a technical perspective is proposed, which is based on the dimensionality of visualization and the type of interaction. Based on this categorization, a comprehensive survey of visual analytics is performed, which examines its evolution from visualization and algorithmic data analysis, and investigates how it is applied in various application domains. In addition, based on the observations and findings gained in this survey, the trends, major challenges, and future directions of visual analytics are discussed.

Multiple Regression Analysis and Frequent Itemset Mining of Electronic Medical Records: A Visual Analytics Approach Using VISA_M3R3

“…The information processing load in a VA system is distributed between the user and the main components of the VA system-namely, the analytics and the interactive visualization modules [65][66][67][68][69][70]. The data analytics module encompasses the computing space and deals with the analysis of data from the information space.…”

Visual Identification of Inconsistency in Pattern

“…In fact, it can rather be seen as an integral approach to decision-making, combining visualisation, human factors and data analysis [13]. Visual analytics from another perspective is a data representation approach that employs interactive visualisation to integrate human judgement into algorithmic data-analysis processes [14]. Thus, visual representation of data plays a vital role in data interpretation and analysis.…”

Dynamic Fuzzy Cognitive Models as a Means of Visual Analytics and Cognitive Graphics

“…Visual analytics is usually applied to the development of user interaction methods and interactive visual tools when working with large volumes of data, contributing to the rapid solution of some analytical problems. Analytical tasks are part of the fastest-growing of all areas of information technology application since the automatic analysis can solve some of these problems [1]. It is applicable in cases where the data is strictly formalized and criteria for their comparison are reasonable.…”

“…Professor D.A. Pospelov formulated three main tasks of cognitive computer graphics [4]: 1. Creation of such models of knowledge representation, in which it would be possible to represent both objects characteristic of logical thinking and image-pictures with which figurative thinking operates with monotonous means.…”