In recent years, large-scale scientific initiatives have spurred the development of affordable lightweight tracking devices such that movement data are now collected in unprecedented quantities for a huge variety of species. Yet, appropriate tools to exploit the full potential of these tracking data are lagging behind.

However, if we really want to capitalize on big movement data we must invest in an enhanced inference, particularly by combining heterogeneous and very high resolution data streams. And we have to pay attention to spatio-temporal patterns in the clustering sequences of movements or behaviours, which have almost virtually been ignored.

To this end, a multidisciplinary consortium was established uniting leading experts in animal behaviour, moving object analysis, space-time or species-distribution modelling, spatio-temporal visualisation, and pattern recognition. By bridging disciplines within and across research areas, this multidisciplinary consortium has both the capacity to promote the development of analytical tools as well as to boost population and community ecology by building a new, integrated framework for the interpretation of state-of-the-art tracking data.

We will follow a sequential approach by initially synthesizing how short-term behavioural responses and phenotypic adjustments within individuals, as well as consistent among-individual differences, impinge on movement ecological processes. This will set the stage for exploiting the full potential of tracking data, to understand behavioural responses, conspecific interactions and decision-making.

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