Development of a visual data storytelling framework

Yangjinbo Zhang

Research output: ThesisDoctoral Thesis

55 Downloads (Pure)

Abstract

This study explores the potential of visual data storytelling as casual visual content. The visual data storytelling framework contributes to the epistemology of data visualisation through a thorough definition of the basic dimensions that are required to tell visual stories based on raw input data. We present quantitative evidence of how the story in visual data content influences the viewer’s cognition and experience towards the data. Our findings shed light on the benefits and limitations of visual data storytelling.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • The University of Western Australia
Supervisors/Advisors
  • Reynolds, Mark, Supervisor
  • Hassan, Mubashar, Supervisor
  • Damjanov, Katarina, Supervisor
  • Lugmayr, Artur, Supervisor
Award date28 Sept 2023
DOIs
Publication statusUnpublished - 2023
  • A Visual Data Storytelling Framework

    Zhang, Y., Reynolds, M., Lugmayr, A., Damjanov, K. & Hassan, G. M., Dec 2022, In: Informatics. 9, 4, 22 p., 73.

    Research output: Contribution to journalArticlepeer-review

    Open Access
    2 Citations (Scopus)
  • Designing a user-centered interactive data-storytelling framework

    Zhang, Y. & Lugmayr, A., 2 Dec 2019, Proceedings of the 31st Australian Conference on Human-Computer-Interaction, OzCHI 2019. Association for Computing Machinery (ACM), p. 428-432 5 p. (ACM International Conference Proceeding Series).

    Research output: Chapter in Book/Conference paperConference paperpeer-review

    4 Citations (Scopus)
  • Converging Data Storytelling and Visualisation

    Zhang, Y., 2018, Entertainment Computing – ICEC 2018: 17th IFIP TC 14 International Conference, Held at the 24th IFIP World Computer Congress, WCC 2018, Proceedings. Clua, E., Roque, L., Lugmayr, A. & Tuomi, P. (eds.). Springer, p. 310-316 7 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11112 LNCS).

    Research output: Chapter in Book/Conference paperConference paperpeer-review

    2 Citations (Scopus)

Cite this