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DIVE: A Graph-Based Visual-Analytics Framework for Big Data

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TLDR
DIVE is a data-agnostic, ontologically expressive software framework that can stream large datasets at interactive speeds that makes novel contributions to structured-data-model manipulation and high-throughput streaming of large, structured datasets.
Abstract
The need for data-centric scientific tools is growing; domains such as biology, chemistry, and physics are increasingly adopting computational approaches. So, scientists must deal with the challenges of big data. To address these challenges, researchers built a visual-analytics platform named DIVE (Data Intensive Visualization Engine). DIVE is a data-agnostic, ontologically expressive software framework that can stream large datasets at interactive speeds. In particular, DIVE makes novel contributions to structured-data-model manipulation and high-throughput streaming of large, structured datasets.

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Data science: Accelerating innovation and discovery in chemical engineering

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An Efficient and Unique TF/IDF Algorithmic Model-Based Data Analysis for Handling Applications with Big Data Streaming

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Visualizing Protein Folding and Unfolding.

TL;DR: A variety of approaches are reviewed, ranging from straightforward to complex and unintuitive for multiscale analysis and visualization of protein folding and unfolding.
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