Collaborative Immersive Analytics for Meteorological and Climatological Data

Jury

• Krzysztof Walczak, Professeur à l’Université d’Économie et de Commerce de Poznań, Pologne, Rapporteur

• Charles Pontonnier, Maître de conférences HDR à l’École Normale Supérieure de Rennes, France,  Rapporteur
• Samir Otmane, Professeur à l’Université d’Évry Paris-Saclay, France, Examinateur
• Christophe Hurter, Professeur à l’École Nationale de l’Aviation Civile, France, Examinateur
• Valérie Gouranton, Maîtresse de conférences HDR à l’INSA Rennes, France,  Examinatrice
• Nicolas Viltard, Maître de conférences à l’Université de Versailles Saint-Quentin-en-Yvelines, France, Examinateur

Résumé

Recent advancements in immersive technologies, such as Head-Mounted Displays (HMDs) in Augmented Reality (AR), have opened new possibilities for collaborative visual analytics. However, leveraging these technologies to enhance data analytics remains challenging due to the complexity and density of data, particularly in fields like meteorology. In this work, we propose novel interaction techniques aimed at improving the selection and analysis of dense data point clouds in AR environments. We also introduce a data integration approach based on Ontology and Linked Data, facilitating efficient querying and filtering during analysis. We evaluated these techniques through a user experimental study using storm and cyclone datasets, which showed promising results for collaborative climate data analysis. Additionally, we proposed and evaluated a spatial partitioning technique for co-located collaborative AR setups. Our findings demonstrate the potential of AR spatial partitioning in immersive analytics for complex data exploration.