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dc.contributor.authorThums, Michele
dc.contributor.authorFernández-Gracia, Juan
dc.contributor.authorSequeira, Ana M. M.
dc.contributor.authorEguíluz, Víctor M.
dc.contributor.authorDuarte, Carlos M.
dc.contributor.authorMeekan, Mark G.
dc.date.accessioned2018-02-14T11:52:53Z
dc.date.available2018-02-14T11:52:53Z
dc.date.issued2018-02-13
dc.identifier.citationThums M, Fernández-Gracia J, Sequeira AMM, Eguíluz VM, Duarte CM, et al. (2018) How Big Data Fast Tracked Human Mobility Research and the Lessons for Animal Movement Ecology. Frontiers in Marine Science 5. Available: http://dx.doi.org/10.3389/fmars.2018.00021.
dc.identifier.issn2296-7745
dc.identifier.doi10.3389/fmars.2018.00021
dc.identifier.urihttp://hdl.handle.net/10754/627134
dc.description.abstractThe rise of the internet coupled with technological innovations such as smartphones have generated massive volumes of geo-referenced data (big data) on human mobility. This has allowed the number of studies of human mobility to rapidly overtake those of animal movement. Today, telemetry studies of animals are also approaching big data status. Here, we review recent advances in studies of human mobility and identify the opportunities they present for advancing our understanding of animal movement. We describe key analytical techniques, potential bottlenecks and a roadmap for progress toward a synthesis of movement patterns of wild animals.
dc.description.sponsorshipAMMS was supported by an ARC Grant DE170100841 and an IOMRC (UWA, AIMS, CSIRO) fellowship. JF-G and VE were supported by Agencia Estatal de Investigación (AEI, Spain) and Fondo Europeo de Desarrollo Regional (FEDER) through project SPASIMM (FIS2016-80067-P AEI/FEDER, UE), and by research funding from KAUST.
dc.publisherFrontiers Media SA
dc.relation.urlhttps://www.frontiersin.org/articles/10.3389/fmars.2018.00021/full
dc.rightsThis is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleHow Big Data Fast Tracked Human Mobility Research and the Lessons for Animal Movement Ecology
dc.typeArticle
dc.contributor.departmentBiological and Environmental Sciences and Engineering (BESE) Division
dc.contributor.departmentMarine Science Program
dc.contributor.departmentRed Sea Research Center (RSRC)
dc.identifier.journalFrontiers in Marine Science
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionAustralian Institute of Marine Science, Indian Ocean Marine Research Centre, University of Western Australia, Crawley, WA, Australia
dc.contributor.institutionInstituto de Física Interdisciplinar y Sistemas Complejos (CSIC-UIB), Palma de Mallorca, Spain
dc.contributor.institutionIOMRC and The UWA Oceans Institute, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
kaust.personDuarte, Carlos M.
refterms.dateFOA2018-06-14T05:17:29Z


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This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Except where otherwise noted, this item's license is described as This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.