Algorithmic Approach to Computational Aesthetics for Creative Data Visualization


Lim, Wei Chuan and Wong, Chee Onn and Wong, Lai Kuan (2022) Algorithmic Approach to Computational Aesthetics for Creative Data Visualization. In: Creative Multimedia Postgraduate Research Colloquium, 14 July 2022, Multimedia University, Malaysia.

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Data visualization is a tool for human to organize, view, and make analysis from a huge set of data. It helps human to explore and discover complicated information that is collectively hidden in the pool of big data. A good presentation of visualization is undoubtedly needed not only to increase the efficiency of data analysis, but more importantly to prevent data loss, which will cause the analyser to reach false conclusions. Computational aesthetic aims to simulate emotions reaching viewers through the senses like visual, audio, tactile and the like. A good aesthetic creation can increase the emotional interest of a visual, thus increasing the chance of conveying the intended message to the target audiences. This project will be focusing on the use of colour as the aesthetic measure and research direction. The objectives are to investigate humans’ perceptions and preferences towards colours and the characteristics of colour combinations, to identify the concerns and prevention in measurable form that need to be considered while choosing colours for data visualization, to propose an algorithmic colour palette creation technique for data visualization diagrams to provide a great aesthetic pleasure, and lastly to measure the effectiveness of the proposed algorithm with existing colour palette creation approaches through user preferences and the performances of information communication. The expected output of this research is computational based aesthetically crafted creative data visualization depending on sets of data, thus the art of data visualization in a better user experienced way utilizing various media and mediums as data visualization platform. This impacts the digital society with big data analytics.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Data visualization, Aesthetic computing, Colour
Subjects: N Fine Arts > N Visual arts
Divisions: Faculty of Creative Multimedia (FCM)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 24 Nov 2022 05:31
Last Modified: 24 Nov 2022 05:31


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