Abstract
Data stories are sequences of data facts connected through a meaningful narrative and combine data visualizations and storytelling to convey information effectively. They have gained popularity due to data journalism, evolving into a hybrid practice involving computer science, design, and storytelling. Creating data stories requires diverse skills however there is a lack of guidance. We found one model that identifies the process of transforming data into visual stories following three stages; explore data, make a story and tell a story. Based on this approach, we surveyed recent literature on data stories in order to classify their contributions to each of the three stages. The contribution of this review is the proposal of guidelines for authors that provide greater detail to each stage and gaps for future research. We hope that by better understanding the design process and the guidelines that emerge from it, we will enrich the quality of the data stories and thus make them more meaningful and engaging to readers.
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