Timothée Jourde
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Timothée Jourde has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- David Auber
University of Bordeaux, CNRS, Bordeaux INP, LaBRI
1 shared publication - Frederic Lalanne
University Bordeaux, CNRS, Bordeaux INP, LaBRI, UMR 5800, Talence, France
1 shared publication - Gaëlle Richer
Universit Paris-Saclay, CNRS, Inria, LISN, France
1 shared publication - Joris Sansen
CBMN UMR 5248, Bordeaux INP, CNRS, Université de Bordeaux, 33600 Pessac, France
1 shared publication - Romain Bourqui
University of Bordeaux
1 shared publication
Latest Publications
- Open Access
- 12 July 2017
- Published by MDPI AG in Informatics
- Vol. 4 (3) , 21
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 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.
- 12 July 2017
- Published by MDPI AG in Informatics
- Vol. 4 (3) , 21
Open AccessVisual 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 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.