Title :
DIVE: A Graph-Based Visual-Analytics Framework for Big Data
Author :
Rysavy, Steven J. ; Bromley, Dennis ; Daggett, Valerie
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.
Keywords :
Big Data; data analysis; data structures; data visualisation; graph theory; ontologies (artificial intelligence); Big Data; DIVE; computational approach; data intensive visualization engine; data-agnostic ontologically expressive software framework; data-centric scientific tools; graph-based visual-analytics framework; high-throughput streaming; structured datasets; structured-data-model manipulation; visual-analytics platform; Big data; Data visualization; Interoperability; Ontologies; Visual analytics; DIVE; Data Intensive Visualization Engine; Dynameomics; big data; bioinformatics; computer graphics; molecular dynamics; ontology; visual analytics;
Journal_Title :
Computer Graphics and Applications, IEEE
DOI :
10.1109/MCG.2014.27