Abstract
The recent availability of affordable and lightweight tracking sensors allows researchers to collect large and complex movement data sets. To explore and analyse these data, applications are required that are capable of handling the data while providing an environment that enables the analyst(s) to focus on the task of investigating the movement in the context of the geographic environment it occurred in. We present an extensible, open-source framework for collaborative analysis of geospatial–temporal movement data with a use case in collective behaviour analysis. The framework TEAMwISE supports the concurrent usage of several program instances, allowing to have different perspectives on the same data in collocated or remote set-ups. The implementation can be deployed in a variety of immersive environments, for example, on a tiled display wall and mobile VR devices.Graphic abstract
Highlights
Animal behaviour as a concept refers to everything animals do, including movement, daily activities, interaction in groups, and underlying mental processes (Seeley and Sherman 2019)
Animal behaviour research investigates a combination of spatial and temporal information for a variety of data: animal movement, with often only position and acceleration samples over time, and sometimes more details such as heading, direction, and wing flapping for birds either measured or derived, static environmental features such as mountains and rivers, slow changing features such as land cover, dynamic
This paper presents TEAMwISE, a web-based framework for animal behaviour analysis in immersive environments, and demonstrates its use in an application case
Summary
Animal behaviour as a concept refers to everything animals do, including movement, daily activities, interaction in groups, and underlying mental processes (Seeley and Sherman 2019). Substantial progress has been made in the development of analysis and visualisation methods and solutions in recent years, for example, regarding the classification and visualisation of trajectories, the classification of behaviour (Demsar et al 2015), and geographic information systems (GIS) Many of those solutions have a particular focus on (visual) analytics, statistics or computational tasks, rather than on an unbiased explorative approach. TEAMwISE supports collaborative data analysis, either collocated in an immersive or in a semi-immersive environment, such as a tiled 2D/3D display wall (TDW, (Sommer et al 2019)), or via shared mobile virtual environments It combines a visualisation of trajectories in the geographic context with movement analysis and supports the synchronised interactive visualisation of multiple views.
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