Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.699412
Title: Narrative construction in information visualisation
Author: Badawood, Donia
ISNI:       0000 0004 5989 5312
Awarding Body: City, University of London
Current Institution: City, University of London
Date of Award: 2015
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Abstract:
Storytelling has been used throughout the ages as means of communication, conveying and transmitting knowledge from one person to another and from one generation to the next. In various domains, formulating of messages, ideas, or findings into a story has proven its efficiency in making them comprehensible, memorable, and engaging. Information Visualization as an academic field also utilises the power of storytelling to make visualizations more understandable and interesting for a variety of audiences. Although storytelling has been a a topic of interest in information visualization for some time, little or no empirical evaluations exist to compare different approaches to storytelling through information visualization. There is also a need for work that addresses in depth some criteria and techniques of storytelling such as transition types in visual stories in general and data-driven stories in particular. Two sets of experiments were conducted to explore how two different models of information visualization delivery influence narratives constructed by audiences. The first model involves direct narrative by a speaker using visualization software to tell a data-story, while the second involves constructing a story by interactively exploring the visualization software. The first set of experiments is a within-subject experiment with 13 participants, and the second set of experiments is a between-subject experiment with 32 participants. In both rounds, an open-ended questionnaire was used in controlled laboratory settings in which the primary goal was to collect a number of written data-stories derived from the two models. The data-stories and answers written by the participants were all analysed and coded using data-driven and pre-set themes. The themes include reported impressions about the story, insight types reported, narrative structures, curiosity about the data, and ease of telling a story after experimenting with each model. The findings show that while the delivery model has no effect on how easy or difficult the participants found telling a data story to be, it does have an effect on the tendency to identify and use outliers' insights in the data story if they are not distracted by direct narration. It also affects the narrative structure and depth of the data story. Examining some more mature domains of visual storytelling, such as films and comics, can be highly beneficial to this new sub-field of data visualization. In the research in hand, a taxonomy of panel-to-panel transitions in comics has been used. The definitions of the components of this taxonomy have been refined to reflect the nature of data-stories in information visualization, and the taxonomy has then been used in coding a number of VAST Challenge videos. The transitions used in each video have been represented graphically with a diagram that shows how the information was added incrementally in order to tell a story that answers a particular question. A number of issues have been taken into account when coding transitions in each video and when designing and creating the visual diagram, such as nested transitions, the use of sub-topics, and delayed transitions. The major contribution of this part of the research is the provision of a taxonomy and description of transition types in the context of narrative visualization, an explanation of how this taxonomy can be used to code transitions in narrative visualization, and a visual summary as a means of summarising that coding. The approaches to data analysis and different storytelling axes, both in the experimental work and in proposing and applying the framework of transition types used, can be usefully applied to other studies and comparisons of storytelling approaches.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.699412  DOI: Not available
Keywords: QA75 Electronic computers. Computer science
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