Visual Exploration of Large Multidimensional Data Using Parallel Coordinates on Big Data Infrastructure

The increase of data collection in various domains calls for an adaptation of methods of visualization to tackle magnitudes exceeding the number of available pixels on screens and challenging interactivity. This growth of datasets size has been supported by the advent of accessible and scalable stor...

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Bibliographic Details
Published in:Informatics (Basel) 2017-09, Vol.4 (3), p.21
Main Authors: Sansen, Joris, Richer, Gaëlle, Jourde, Timothée, Lalanne, Frédéric, Auber, David, Bourqui, Romain
Format: Article
Language:English
Subjects:
big data
Computer Science
Computing time
Data acquisition
Data management
distributed computing
Exploration
Hybrid systems
Infrastructure
interactive data exploration and discovery
Interactive systems
Multidimensional data
parallel coordinates
Screens
Visualization
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Summary:The increase of data collection in various domains calls for an adaptation of methods of visualization to tackle magnitudes exceeding the number of available pixels on screens and challenging interactivity. This growth of datasets size has been supported by the advent of accessible and scalable storage and computing infrastructure. Similarly, visualization systems need perceptual and interactive scalability. We present a complete system, complying with the constraints of aforesaid environment, for visual exploration of large multidimensional data with parallel coordinates. Perceptual scalability is addressed with data ion while interactions rely on server-side data-intensive computation and hardware-accelerated rendering on the client-side. The system employs a hybrid computing method to accommodate pre-computing time or space constraints and achieves responsiveness for main parallel coordinates plot interaction tools on billions of records.
ISSN:2227-9709
2227-9709
DOI:10.3390/informatics4030021