Title :
Gestalt Principles in Multimodal Data Representation
Author :
Rosli, Muhammad Hafiz Wan ; Cabrera, Andres
Author_Institution :
Univ. of California, Santa Barbara, Santa Barbara, CA, USA
Abstract :
Data visualization is a powerful tool to communicate data in a clear, digestible format through graphical means. To be effective, however, form and function need to work in tandem, filtering layers of noise to reveal the key aspects of the analyzed data. Indeed, this could prove to be sufficient in discovering already known patterns. Still, the search for undiscovered patterns would require the full dataset to be presented as a whole, which bears the risk of sensory overload. Human sensory systems function as a systemic unit in relation to one another, dynamically sampling the signals around us to give a concise scene analysis. To decipher a complex, multidimensional dataset, a representational system that is able to reproduce the layers of information through different stimulations would be required. This article explores the possibilities of using multimodal data representation as a method to communicate multidimensional data, guided by the principles of Gestalt psychology. Point Cloud, an artwork that implements such explorations through the visualization and sonification of lightning data is presented as an application of this research. The Web extra can be found at http://youtu.be/pQtxsvgv80E.
Keywords :
cryptography; data structures; data visualisation; pattern recognition; Gestalt psychology; concise scene analysis; data visualization; decipher; graphical means; multimodal data representation; point cloud; undiscovered patterns; Cloud computing; Data visualization; Granular synthesis; Psychology; Sonification; Gestalt psychology; Point Cloud; computer graphics; granular synthesis; multimodal; pointillism; sonification; visualization;
Journal_Title :
Computer Graphics and Applications, IEEE
DOI :
10.1109/MCG.2015.29