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 beenbecome essential tasks in many elds of studies, such as health, biology, chemistry, social science, astronomy,and physics. However, compared with the development of data storage and management technologies, ourability to gain useful information from the collected data does not match our ability to collect the data. Thisgap has led to a surge of research activity in the eld of visual analytics. Visual analytics employs interactivevisualization to integrate human judgment into algorithmic data-analysis processes. In this paper, the aim isto draw a complete picture of visual analytics to direct future research by examining the related research invarious 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
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