Overview of visual analytics

A. Chopra, R. Samant
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Abstract

Visual analytics is "the science of analytical reasoning facilitated by visual interactive interfaces." It can attack certain problems whose size, complexity, and need for closely coupled human and machine analysis may make them otherwise intractable. Visual analytics advances science and technology developments in analytical reasoning, interaction, data transformations and representations for computation and visualization, analytic reporting, and technology transition. As a research agenda, visual analytics brings together several scientific and technical communities from computer science, information visualization, cognitive and perceptual sciences, interactive design, graphic design, and social sciences. This science of analytical reasoning provides the reasoning framework upon which one can build both strategic and tactical visual analytics technologies for threat analysis, prevention, and response. Visual Analytics is a relatively new multidisciplinary field that combines various research areas including knowledge discovery, data analysis, visualization, human-computer interaction, data management, geo-spatial and temporal data processing and statistics. Visual Analytics has seen unprecedented growth in the past five years and is expected to grow ten folds in the coming future seeing the amount of massive, dynamic and heterogeneous data which concludes nothing unless put to use using the visual analytical techniques. The basic goal of visual analytics includes deriving an insight from the large amount of dynamic data which is from different sources and to analyze them to discover the unexpected and provide timely, defensible, and understandable assessments which can be then communicated effectively for action. An integration of the increasing processing power of computers with the efficient pattern recognition abilities and domain knowledge of human analysts is a challenging and promising road in dealing with large amounts of complex data. It will be also a major driving force for solutions for information overload in many research and commercial areas.
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视觉分析概述
视觉分析是“通过视觉交互界面促进分析推理的科学”。它可以解决某些问题,这些问题的规模、复杂性以及对人与机器紧密耦合分析的需求可能会使它们变得难以处理。可视化分析推动了科学和技术在分析推理、交互、数据转换和计算和可视化表示、分析报告和技术转换方面的发展。作为一项研究议程,视觉分析汇集了来自计算机科学、信息可视化、认知和感知科学、交互设计、图形设计和社会科学的几个科学和技术社区。这门分析推理科学提供了一个推理框架,在这个框架上,人们可以构建战略和战术视觉分析技术,用于威胁分析、预防和响应。视觉分析是一个相对较新的多学科领域,它结合了各种研究领域,包括知识发现、数据分析、可视化、人机交互、数据管理、地理空间和时间数据处理和统计。视觉分析在过去的五年中经历了前所未有的增长,预计在未来将增长十倍,因为大量的、动态的和异构的数据,除非使用视觉分析技术,否则将一无所获。可视化分析的基本目标包括从来自不同来源的大量动态数据中获得洞察力,并对其进行分析,以发现意想不到的情况,并提供及时、可辩护和可理解的评估,然后可以有效地沟通以采取行动。将计算机日益增强的处理能力与人类分析人员高效的模式识别能力和领域知识相结合,是处理大量复杂数据的一条具有挑战性和前景的道路。它也将成为许多研究和商业领域解决信息过载的主要推动力。
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