Analysis and visualisation of movement : an interdisciplinary review
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The processes that cause and influence movement are one of the main points of enquiry in movement ecology. However, ecology is not the only discipline interested in movement: a number of information sciences are specialising in analysis and visualisation of movement data. The recent explosion in availability and complexity of movement data has resulted in a call in ecology for new appropriate methods that would be able to take full advantage of the increasingly complex and growing data volume. One way in which this could be done is to form interdisciplinary collaborations between ecologists and experts from information sciences that analyse movement. In this paper we present an overview of new movement analysis and visualisation methodologies resulting from such an interdisciplinary research network: the European COST Action “MOVE - Knowledge Discovery from Moving Objects” (http://www.move-cost.info webcite). This international network evolved over four years and brought together some 140 researchers from different disciplines: those that collect movement data (out of which the movement ecology was the largest represented group) and those that specialise in developing methods for analysis and visualisation of such data (represented in MOVE by computational geometry, geographic information science, visualisation and visual analytics). We present MOVE achievements and at the same time put them in ecological context by exploring relevant ecological themes to which MOVE studies do or potentially could contribute.
Demsar , U , Buchin , K , Cagnacci , F , Safi , K , Speckmann , B , Van de Weghe , N , Weiskopf , D & Weibel , R 2015 , ' Analysis and visualisation of movement : an interdisciplinary review ' Movement Ecology , vol 3 , no. 5 . DOI: 10.1186/s40462-015-0032-y
© 2015 Demšar et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
This paper presents the interdisciplinary methodological developments resulting from the COST Action IC0903, “MOVE: Knowledge Discovery from Moving Objects” (http://www.move-cost.info/). Funding from the COST Program (European Cooperation in Science and Technology) is gratefully acknowledged, as are the many contributions made by the MOVE participants to the results of this COST action.
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