Visualization of Large-Scale Distributed Data

Abstract

An effective visualization is best achieved through the creation of a proper representation of data and the interactive manipulation and querying of the visualization. Large-scale data visualization is particularly challenging because the size of the data is several orders of magnitude larger than what can be managed on an average desktop computer. Large-scale data visualization therefore requires the use of distributed computing. By leveraging the widespread expansion of the Internet and other national and international high-speed network infrastructure such as the National LambdaRail, Internet-2, and the Global Lambda Integrated Facility, data and service providers began to migrate toward a model of widespread distribution of resources. This chapter introduces different instantiations of the visualization pipeline and the historic motivation for their creation. The authors examine individual components of the pipeline in detail to understand the technical challenges that must be solved in order to ensure continued scalability. They discuss distributed data management issues that are specifically relevant to large-scale visualization. They also introduce key data rendering techniques and explain through case studies approaches for scaling them by leveraging distributed computing. Lastly they describe advanced display technologies that are now considered the “lenses” for examining large-scale data.

Blockchain-based green big data visualization: BGbV

“…Modern IoT systems involve complex interaction among different entities, demanding a secure, efficient, and distributed infrastructure. Therefore, distributed data visualization is considered an excellent solution to achieve perception and overview of this multi-dimensional massive data [19]. Big data visualization is different from the conventional visualization of data.…”