Temporal Exploration with Raster Algorithm as Novel Visualization Algorithms
Analyzing massive and complex datasets is essential to making new discoveries and creating benefits for people, but it remains a very difficult task; most data have become simply too large and often have too short a lifespan, i.e. they change too rapidly, for classical visualization or analysis methods to handle it properly. This is particularly important for movement data, such as traffic data on roads or in airspace, because of their intrinsic time-dependent nature. The key to supporting this task is not only to visualize data, but also to allow users to interact with them. The goal of TERANoVA is to explore new computing techniques called pixel-based algorithms so as to support efficient interactive visualizations for the exploration of large datasets of time-dependent data. This basic research project, at the crossroads of Information Visualization, Visual Analytics, Computer Graphics and Human Computer Interaction, will contribute to the development of solutions for making big data a tool for everyone.
Appel à projets générique 2014Défi 7: Sociétés de l’information et de la communication JCJC 2014 (Jeune Chercheuse Jeune Chercheur) / 42 months Coordinating partner: Christophe Hurter Ecole Nationale de l’Aviation Civile (ENAC), Toulouse, France
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The P.I. acknowledges the support of the French Agence Nationale de la Recherche (ANR):
grants ANR-14-CE24-0006-01 (project TERANOVA).