KEYWORDS: Visualization, Visual analytics, 3D modeling, Virtual reality, Data processing, 3D displays, Data analysis, Scientific visualization, Displays, Human-machine interfaces
Advancement in the areas of high performance computing and computational sciences have facilitated the generation of an enormous amount of research data by computational scientists - the volume, velocity and variability of Big 'Research' Data has increased across all disciplines. An immersive and non-immersive analytics platform capable of handling extreme-scale scientific data will enable scientists to visualize unwieldy simulation data in an intuitive manner and guide the development of sophisticated and targeted analytics to obtain usable information. Our immersive and non-immersive visualization work is an attempt to provide computational scientists with the ability to analyze the extreme-scale data generated. The main purpose of this paper is to identify different characteristics of a scientific data analysis process to provide a general outline for the scientists to select the appropriate visualization systems to perform their data analytics. In addition, we will include some of the details on how to how the immersive and non-immersive visualization hardware and software are setup. We are confident that the findings in our paper will provide scientists with a streamlined and optimal visual analytics workflow.
Major advancements in computational and sensor hardware have enormously facilitated the generation and collection of research data by scientists - the volume, velocity and variety of Big ’Research’ Data has increased across all disciplines. A visual analytics platform capable of handling extreme-scale data will enable scientists to visualize unwieldy data in an intuitive manner and guide the development of sophisticated and targeted analytics to obtain useable information. Reconfigurable Visual Computing Architecture is an attempt to provide scientists with the ability to analyze the extreme-scale data collected. Reconfigurable Visual Computing Architecture requires the research and development of new interdisciplinary technological tools that integrate data, realtime predictive analytics, visualization, and acceleration on heterogeneous computing platforms. Reconfigurable Visual Computing Architecture will provide scientists with a streamlined visual analytics tool.
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