In-situ data analytics offers an environment rich in contextual information that supports informed decision-making. Examples range from industrial applications, such as factory machinery data, through to environmental data. Despite these benefits, in-situ data analytics is inflexible and unsustainable due to the travel it requires.

This project leverages innovative spatial computing technologies to bring the context to the analyst's workspace, creating an immersive contextual data analytics environment. With the rapid development of virtual and augmented reality technologies, along with 3D scene reconstruction techniques, such an approach has become more feasible than ever. The project aims to better understand this new concept through a series of experiments examining different design factors and success measures.