Understanding the Use of Narrative Patterns by Novice Data Storytellers

Tom Blount, Laura Koesten, Yuchen Zhao, Elena Simperl

Abstract

Data stories are about communicating data, tailored to a specific audience, with a compelling narrative. Creating them requires a mix of data science and design skills, which can be difficult for beginners. Patterns can help, as they provide tried-and-tested solutions to commonly occurring challenges. ‘Narrative patterns’ are a particular class of patterns that support data-storytellers in structuring the presentation of data within their story, aiding them in effectively communicating with their audience. Our aim is to understand how such patterns are applied in practice and identify ways they could be of greater use, especially for people new to the field. To this end, we conduct a review of 67 data stories, created by both professional data storytellers and by postgraduate university students studying data-science, to analyse their use of narrative patterns. Starting from a collection of narrative patterns from the literature, we explore which patterns are used more often, either on their own or in combination, and which ones beginners struggle with. From the findings we derive recommendations on how to refine some of the less accessible patterns and for training and tool support, which would allow wider audiences to articulate their data insights effectively.

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