ADVISU : interactive visualization of anomalies and dependencies from massive scientific datasets

Noël Novelli (1) , Laure Berti-Équille (1, 2) , Christophe Hurter (3, 4)

1 LIF - Laboratoire d'informatique Fondamentale de Marseille - UMR 6166
2 IRD - Institut de Recherche pour le Développement
3 IRIT - Institut de recherche en informatique de Toulouse
4 LII - ENAC - Equipe Informatique Interactive

In this demo, we present ADVISU (Anomaly and Dependency VISUalization), a powerful interactive system for visual analytics from massive datasets. ADVISU efficiently computes different types of dependencies (FDs, CFDs) and detects data anomalies from databases of large size, i.e., up to several thousands of attributes and millions of records. Real-time and scalable computational methods have been implemented in ADVISU to ensure interactivity and the demonstration is intended to show how these methods scale up for realworld massive scientific datasets in astrophysical and oceanographic application domains. ADVISU provides the users informative and interactive graphical interfaces for visualizing data dependencies and anomalies. It enables the analysis to be refined interactively while recomputing the dependencies and anomalies in user selected subspaces with good performance.

Domaines: Interface homme-machine [cs.HC]

Noël Novelli, Laure Berti-Équille, Christophe Hurter. ADVISU : interactive visualization of anomalies and dependencies from massive scientific datasets. EGC 2012, 12ème Conférence Internationale Francophone sur l'Extraction et la Gestion des Connaissances, Jan 2012, Bordeaux, France. ⟨hal-00879080⟩