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

LaBRI, UMR 5800, Université de Bordeaux, 351, cours de la Libération F-33405 Talence cedex, France
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Academic Editors: Achim Ebert and Gunther H. Weber
Informatics 2017, 4(3), 21; https://doi.org/10.3390/informatics4030021
Received: 31 May 2017 / Revised: 30 June 2017 / Accepted: 10 July 2017 / Published: 12 July 2017
(This article belongs to the Special Issue Scalable Interactive Visualization)
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 abstraction 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. View Full-Text
Keywords: big data; multidimensional data; parallel coordinates; interactive data exploration and discovery; distributed computing big data; multidimensional data; parallel coordinates; interactive data exploration and discovery; distributed computing
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MDPI and ACS Style

Sansen, J.; Richer, G.; Jourde, T.; Lalanne, F.; Auber, D.; Bourqui, R. Visual Exploration of Large Multidimensional Data Using Parallel Coordinates on Big Data Infrastructure. Informatics 2017, 4, 21.

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