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Cognitively plausible information visualization


Fabrikant, Sara I; Skupin, André (2005). Cognitively plausible information visualization. In: Dykes, Jason; MacEachren, Alan M; Kraak, Menno-Jan. Exploring Geovisualization. Amsterdam NL: Elsevier, 667-690.

Abstract

This chapter proposes a framework for the construction of cognitively plausible semantic information spaces and emphasizes on the ways in which the framework may be applied towards the design of cognitively adequate spatializations. A cognitively plausible Information Visualization is designed such that it matches human's internal visualization capabilities. The proposed framework focuses on the use of geographic space as a data generalization strategy (ontology) and the use of spatial representations or maps to depict these data abstractions. The building blocks of this spatialization framework are informed by geographic information theory and include principles of ontological modeling such as semantic generalization (spatial primitives), geometric generalization (visual variables), association (source–target domain mapping through spatial metaphors), and aggregation (hierarchical organization). Spatialization is defined as a data transformation method based on spatial metaphors, with the aim of generating a cognitively adequate graphic representation for data exploration and knowledge discovery in multi-dimensional databases. Spatialization not only provides the construction of visual descriptions and summaries of large data repositories but also creates opportunities for visual queries and sense-making approaches.

Abstract

This chapter proposes a framework for the construction of cognitively plausible semantic information spaces and emphasizes on the ways in which the framework may be applied towards the design of cognitively adequate spatializations. A cognitively plausible Information Visualization is designed such that it matches human's internal visualization capabilities. The proposed framework focuses on the use of geographic space as a data generalization strategy (ontology) and the use of spatial representations or maps to depict these data abstractions. The building blocks of this spatialization framework are informed by geographic information theory and include principles of ontological modeling such as semantic generalization (spatial primitives), geometric generalization (visual variables), association (source–target domain mapping through spatial metaphors), and aggregation (hierarchical organization). Spatialization is defined as a data transformation method based on spatial metaphors, with the aim of generating a cognitively adequate graphic representation for data exploration and knowledge discovery in multi-dimensional databases. Spatialization not only provides the construction of visual descriptions and summaries of large data repositories but also creates opportunities for visual queries and sense-making approaches.

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Additional indexing

Item Type:Book Section, not_refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Scopus Subject Areas:Physical Sciences > General Computer Science
Language:English
Date:2005
Deposited On:31 Jan 2020 10:30
Last Modified:22 Apr 2020 22:51
Publisher:Elsevier
ISBN:978-0-08-044531-1
OA Status:Closed
Publisher DOI:https://doi.org/10.1016/b978-008044531-1/50453-x

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