ILDA - Interacting with Large DAta

Research Themes

Novel Forms of Display for Groups and Individuals. Data sense-making and analysis is not limited to individual users working with a single device, but increasingly involves multiple users working together in a coordinated manner in multi-display environments: workstations, wall displays, handheld devices, mixed reality. We investigate how to empower users working with complex data by leveraging novel types of displays and combinations of displays, designing visualizations adapted to their capabilities. More...

Novel Forms of Input for Groups and Individuals. The contexts in which novel types of displays are used often call for novel types of input. We design and evaluate interaction techniques that take advantage of input technologies such as tactile surfaces, 3D motion trackers and custom physical controllers built on-demand. We investigate input techniques that feature a high level of expressive power, as well as techniques that improve group awareness and support strongly-coupled cooperative tasks. More...

Interacting with Spatio-Temporal Data. Spatio-temporal data often play a key role in sense-making and decision-making processes in domains such as, e.g., environmental resource management, transportation, data journalism, and the scientific analysis of natural phenomena. We research novel visualization and interaction techniques, aiming to support different user communities with both desktop tools and more situated visualizations in Augmented Reality. In particular we devise techniques to integrate multivariate data in the proper geo-spatial representations, providing users with effective means to manipulate those data. More...

Application Areas

Mission-critical Systems. Mission-critical contexts of use include emergency response & management; critical infrastructure operations such as public transportation systems, communications and power distribution networks; and the operation of large scientific instruments such as astronomical observatories and particle accelerators. Central to these contexts of work is the notion of situation awareness. Our goal is to investigate novel ways of interacting with computing systems that improve collaborative data analysis capabilities and decision support assistance in a mission-critical, often time-constrained, work context. More...

Exploratory Analysis of Scientific Data. Many scientific disciplines are increasingly data-driven, including astronomy, molecular biology, particle physics, or neuroanatomy. No matter their origin (experiments, remote observations, large-scale simulations), these data can be difficult to understand and analyze because of their sheer size and complexity. Our goal is to investigate how data-centric interactive systems can improve collaborative scientific data exploration. More...