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Designing geovisual analytics environments and displays with humans in mind / Arzu Çöltekin in ISPRS International journal of geo-information, vol 8 n° 12 (December 2019)  

Public [article]  inISPRS International journal of geo-information > vol 8 n° 12 (December 2019) . - n° 572 Titre : Designing geovisual analytics environments and displays with humans in mind Type de document : Article/Communication Auteurs : Arzu Çöltekin, Auteur ; Sidonie Christophe , Auteur ; Anthony Robinson, Auteur ; Urška Demšar, Auteur Année de publication : 2019 Projets : 1-Pas de projet / Article en page(s) : n° 572 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse visuelle [Termes IGN] interface homme-machine [Termes IGN] langage naturel (informatique) [Termes IGN] réalité virtuelle [Termes IGN] représentation cartographique 3D [Vedettes matières IGN] Géovisualisation Résumé : (Auteur) [Introduction] In this open-access Special Issue, we feature a set of publications under the theme “Human-Centered Geovisual Analytics and Visuospatial Display Design”. As the title suggests, the scope of this collection is on human-centered questions regarding visual analytics software environments; and the design of visuospatial displays within and beyond these environments. The essential building blocks of visual analytics (VA) are computers and humans [1]. Without computers (i.e., technology and quantitative methods such as those used in statistics and data science) VA simply would not exist. For decades now, it has been clear that computers are better than humans in processing large amounts of data, being capable of storing and quickly retrieving what is needed. Mechanisms such as parsing and filtering, automated pattern detection and machine learning, manual queries, and coordinated-view visualizations make visual analytics environments amazingly versatile and powerful [2]. The tools contained in VA environments assist us in spatial learning, discovery, and decision making [3,4]. It is important to remember that they can really only play an assistive role however, because tasks such as learning, interpreting patterns to make discoveries, and decision making are inherently qualitative. Often the goal is to make decisions based on observed patterns and anomalies. Such patterns and anomalies are much more likely to emerge (and if they are known to exist, they are better expressed) with visualizations than via numbers or tables alone [5]. Numéro de notice : A2019-614 Affiliation des auteurs : LASTIG COGIT+Ext (2012-2019) Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi8120572 Date de publication en ligne : 11/12/2019 En ligne : https://doi.org/10.3390/ijgi8120572 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95213 [article]