Big Data Visualization and Visual Analytics.
Approaches and Trends
Abstract: In our days, in more and more areas, huge volumes of data – that are continuously growing – are collected and stored. The possibility of effectively using them, by extracting the useful contained information, becomes an increasing challenge. The visual analytics (VA) field tries to provide better and more effective means for humans to analyze and understand such huge data sets, thus enabling them to decide and act accordingly in real time. This paper presents an overview on what we are calling today visual analytics, with specific approaches and trends. Aspects regarding the integration of Big Data visualization techniques, data management technologies, automated methods for data mining and analytics, with human user interaction for steering the chain of processings and actions specific to visual analytics to find and extract useful information and knowledge for evaluations that may support immediate decisions and actions, are covered. The main ideas regarding the definition, method / process, and components of the visual analytics, resulted from the VisMaster Project, a Coordination Action in the FET program of EU’s FP7 for R&D, are briefly reproduced. Some of the major application areas are reviewed. Also, the current status is presented, through some open source and comercial products, and an overview of the approaches and trends in VA, with problems, challenges, opportunities and potential solutions, is summarized. Some conclusions are finally presented.
Keywords: Data Visualization, Big Data, Visual Analytics, Visual Data Mining, Data Management.
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