Narrative Design Patterns for Data-Driven Storytelling

Benjamin Bach, D. Stefaner, J. Boy, S. Drucker, L. Bartram, J. Wood, P. Ciuccarelli, Yuri Engelhardt, U. Köppen, B. Tversky

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review


This chapter introduces the concept of narrative design patterns, that aim to facilitate the shaping of compelling data-driven stories. There are many different ways storytellers can narrate the same story, depending on their intentions and their audience. Here, the authors define and describe a set of these narrative design patterns that can be used on their own or in combination to tell data stories in a myriad of ways. The authors then analyze 18 of them, and illustrate how these patterns can help storytellers think about the stories they want to tell and the best ways to narrate them. Each pattern has a specific purpose, for example, engaging the audience, evoking empathy, or creating flow and rhythm in the story. The authors assume storytellers already know what story they want to tell, why they want to tell it, and who they want to tell it to. These patterns may not only facilitate the process of creating compelling narratives, but stimulate a wider discussion on techniques and practices for data-driven storytelling.
Original languageEnglish
Title of host publicationData-Driven Storytelling
EditorsN. Riche, C. Hurter, N. Diakopoulos, S. Carpendale
PublisherCRC Press (Taylor & Francis)
ISBN (Electronic)9781315281575
Publication statusPublished - 2018

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