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Pyramidal framework: guidance for the next generation of GIS spatial-temporal models / Cyril Carré in ISPRS International journal of geo-information, vol 10 n° 3 (March 2021)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 3 (March 2021) . - n° 188 Titre : Pyramidal framework: guidance for the next generation of GIS spatial-temporal models Type de document : Article/Communication Auteurs : Cyril Carré, Auteur ; Younes Hamdani, Auteur Année de publication : 2021 Article en page(s) : n° 188 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] cadre conceptuel [Termes IGN] données spatiotemporelles [Termes IGN] événement [Termes IGN] modèle conceptuel de données spatio-temporelles [Termes IGN] point de vue [Termes IGN] prise en compte du contexte [Termes IGN] SIG dynamique Résumé : (auteur) Over the last decade, innovative computer technologies and the multiplication of geospatial data acquisition solutions have transformed the geographic information systems (GIS) landscape and opened up new opportunities to close the gap between GIS and the dynamics of geographic phenomena. There is a demand to further develop spatio-temporal conceptual models to comprehensively represent the nature of the evolution of geographic objects. The latter involves a set of considerations like those related to managing changes and object identities, modeling possible causal relations, and integrating multiple interpretations. While conventional literature generally presents these concepts separately and rarely approaches them from a holistic perspective, they are in fact interrelated. Therefore, we believe that the semantics of modeling would be improved by considering these concepts jointly. In this work, we propose to represent these interrelationships in the form of a hierarchical pyramidal framework and to further explore this set of concepts. The objective of this framework is to provide a guideline to orient the design of future generations of GIS data models, enabling them to achieve a better representation of available spatio-temporal data. In addition, this framework aims at providing keys for a new interpretation and classification of spatio-temporal conceptual models. This work can be beneficial for researchers, students, and developers interested in advanced spatio-temporal modeling. Numéro de notice : A2021-315 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.3390/ijgi10030188 Date de publication en ligne : 22/03/2021 En ligne : https://doi.org/10.3390/ijgi10030188 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97891 [article]