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Towards a SpatioTemporal Data Model for Traditional Ecological Knowledge/Indigenous Knowledge

Bibliographic Data

ID14701580
AuthorsKierin Mackenzie (0000-0002-7011-3049, University of Canterbury, corresponding author), John Pirker (University of Canterbury), Femke Reitsma (University of Canterbury)
Year2020
Volume55
Issue1
Pages29-41
Publication date2020-03-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueCartographica The International Journal for Geographic Information and Geovisualization (JOURNAL)
Journal identifiersISSN: 0317-7173 • E-ISSN: 1911-9925
PublisherUniversity of Toronto Press Inc. (UTPress) (PUBLISHER)
DOI10.3138/cart-2017-0027
OpenAlexW3011847282
LanguageEN
Citations received1
References cited41

Indigenous peoples have been making maps and utilizing GIS for some time, and have been mapped and cadastralized for some time as well. Models of Indigenous spatiality have been the topic of some work, but the data for modelling Indigenous spatiotemporality remain scant, and the subject matter is rich. This paper suggests another layer of representation for GIS when dealing with complex data with a strong relational and qualitative component. In this paper, we present a new data model that we are calling the spatiotemporal motif. It is an open data model incorporating choric (coordinate) as well as topic (attribute) space and chronic (coordinate) as well as kairic (attribute) time. The model aims to fill gaps in other data model depictions concerning lack of support for cyclical time, multiple constraints on what constitutes a proper time or place for a given activity, fluid and dynamic spatiotemporal boundaries, support for narratives and contingencies, and privacy and sensitivity concerns

Component (thermodynamics · Data mining · Data model (GIS · Data modeling · Data science · Geography · Indigenous · Motif (music · Narrative · Representation (politics · Traditional knowledge · Computer Science · Conservation, Biodiversity, and Resource Management · Geographic Information Systems Studies · Indigenous Knowledge Systems and Agriculture · Artificial Intelligence · Ecology

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Unique citing works1
Citations per year0,25
Citation span2022 - 2022 (1)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 1

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