Publications by authors named "Stefan P Feyer"

Animal behaviour is often modelled as networks, where, for example, the nodes are individuals of a group and the edges represent behaviour within this group. Different types of behaviours or behavioural categories are then modelled as different yet connected networks which form a multilayer network. Recent developments show the potential and benefit of multilayer networks for animal behaviour research as well as the potential benefit of stereoscopic 3D immersive environments for the interactive visualisation, exploration and analysis of animal behaviour multilayer networks.

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Article Synopsis
  • Researchers examined how the arrangement of layers in a multilayer network (MLN) affects readability and analysis tasks.
  • They conducted a study using a Virtual Reality headset to test 2D, 2.5D, and 3D arrangements across six different analysis tasks.
  • While there wasn't a definitive best arrangement, the study provided data-driven recommendations for effectively using each arrangement type based on specific analysis tasks.
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Understanding the movement of animals is important for a wide range of scientific interests including migration, disease spread, collective movement behaviour and analysing motion in relation to dynamic changes of the environment such as wind and thermal lifts. Particularly, the three-dimensional (3D) spatial-temporal nature of bird movement data, which is widely available with high temporal and spatial resolution at large volumes, presents a natural option to explore the potential of immersive analytics (IA). We investigate the requirements and benefits of a wide range of immersive environments for explorative visualization and analytics of 3D movement data, in particular regarding design considerations for such 3D immersive environments, and present prototypes for IA solutions.

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