Visual Representation and Cognitive Models in Information Visualization

¹ City Graduate School, City University Malaysia, Kuala Lumpur 46100, Malaysia; College of Design and Fine Arts, Qingdao Huanghai University, Qingdao 266427, China,

² Faculty of Creative Industries, City University Malaysia, Kuala Lumpur 46100, Malaysia,

JERA 2024 , 8(4), 115–120; https://doi.org/10.26689/jera.v8i4.7923

© 2024 by the Authors. Licensee Whioce Publishing, Singapore. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )

Abstract

As a branch of computer science, information visualization aims to help users understand and analyze complex data through graphical interfaces and interactive technologies. Information visualization primarily includes various visual structures such as time-series structures, spatial relationship structures, statistical distribution structures, and geographic map structures, each with unique functions and application scenarios. To better explain the cognitive process of visualization, researchers have proposed various cognitive models based on interaction mechanisms, visual perception steps, and novice use of visualization. These models help understand user cognition in information visualization, enhancing the effectiveness of data analysis and decision-making.

References

Zhang L, 2021, Analysis of User Interface Animation Design in Digital Media Art. Art and Design, 08: 45–48. https://doi.org/10.16824/j.cnki.issn10082832.2021.08.021

Wang N, Qiu X, 2021, Simulation of UI Interface Data Visualization Transmission Based on Perceptual Feedback. Computer Simulation, 38(10): 34–36.

Jason F, 2012, The Mobile Interface Theory: Embodied Space and Locative Media. Routledge, London, 2012: 56–60.

Xu H, 2017, Study on the Styling Style Characteristics in Dynamic Graphic Design. Packaging World, 05: 120–121. https://doi.org/10.13337/j.cnki.packaging.world.2017.05.040

Shi S, Cheng X, Hof PMJVD, 2020, Excitation Allocation for Generic Identifiability of a Single Module in Dynamic Networks: A Graphic Approach. IFAC-PapersOnLine, 53(2): 40–45.

Liu Y, Zhang Y, 2022, Research on Dynamic Graphics Features in Digital Media Interface. Digital Communication World, 5: 121–123.

Spiliotopoulos D, Tzoannos E, Stavropoulou P, et al., 2012, Designing User Interfaces for Social Media Driven Digital Preservation and Information Retrieval. Springer-Verlag Berlin Heidelberg, 7382: 581–584.

Previous article in this issue

Next article in this issue