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dc.contributor.author
 hal.structure.identifier
MACKENZIE, Kierin
300998 University of Canterbury [Christchurch]
dc.contributor.authorSIABATO, Willington
dc.contributor.author
 hal.structure.identifier
REITSMA, Femke
300998 University of Canterbury [Christchurch]
dc.contributor.author
 hal.structure.identifier
CLARAMUNT, Christophe
13094 Institut de Recherche de l'Ecole Navale [IRENAV]
dc.date.accessioned2017
dc.date.available2017
dc.date.issued2017
dc.date.submitted2017
dc.identifier.issn0972-4923
dc.identifier.urihttp://hdl.handle.net/10985/11776
dc.description.abstractTraditional Ecological Knowledge (TEK) has been at the centre of mapping efforts for decades. Indigenous knowledge (IK) is a critical subset of TEK, and Indigenous peoples utilize a wide variety of techniques for keeping track of time. Although techniques for mapping and visualizing the temporal aspects of TEK/IK have been utilized, the spatio-temporal dimensions of TEK are not well explored visually outside of seasonal data and narrative approaches. Existing spatio-temporal models can add new visualization approaches for TEK but are limited by ontological constraints regarding time, particularly the poor support for multi-cyclical data and localized timing. For TEK to be well represented, flexible systems are needed for modelling and mapping time that correspond well with traditional conceptions of time being supported. These approaches can take cues from previous spatio-temporal visualization work in the GIS community, and from temporal depictions extant in existing cultural traditions.
dc.language.isoen
dc.publisherMedknow Publications
dc.rightsPost-print
dc.subjectVisualization
dc.subjectSpatio-temporal data
dc.subjectTraditional ecological knowledge (TEK)
dc.subjectIndigenous knowledge (IK)
dc.subjectCyclical time
dc.subjectModelling
dc.subjectData exploration
dc.titleSpatio-temporal visualisation and data exploration of traditional ecological knowledge/indigenous knowledge
dc.identifier.doi10.4103/0972-4923.201391
dc.typdocArticle dans une revue avec comité de lecture
dc.localisationCentre de Paris
dc.subject.halInformatique: Intelligence artificielle
dc.subject.halInformatique: Modélisation et simulation
dc.subject.halSciences de l'environnement: Environnement et Société
dc.subject.halSciences de l'Homme et Société: Sciences de l'information et de la communication
ensam.audienceInternationale
ensam.page41-58
ensam.journalConservation and Society
ensam.volume15
ensam.issue1
ensam.peerReviewingOui
hal.identifierhal-01527576
hal.version1
hal.statusaccept


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