Using generative <scp>AI</scp> to co‐design data‐driven stories

Abstract Data storytelling combines communication and visualization techniques with storytelling principles to convey insights meaningfully and engagingly. This paper introduces the AI‐DIKW framework, an extension of the Story Data–Information–Knowledge–Wisdom (S‐DIKW) hierarchy, designed to support the co‐creation of data‐driven stories by combining human expertise with Generative AI. The AI‐DIKW framework extends the S‐DIKW model through the application of the journalistic 5‐Ws, which guide Generative AI to provide consistent and contextually relevant outputs. This study describes how Generative AI can contribute to the iterative construction of a story's key components while ensuring alignment with ethical principles. Applying Generative AI at the AI‐Data stage involves extracting insights from the data. Applying Generative AI at the AI‐Information stage means enriching the insight with relevant context, while at the AI‐Knowledge stage, Generative AI helps the data storyteller to enrich the story with meaningful next steps, anchored to a selected ethical framework. Finally, at the AI‐Wisdom stage, Generative AI helps the data storyteller to tailor the story to specific audiences. At each stage of the AI‐DIKW framework, Generative AI acts as a co‐designer that helps the data storyteller to frame and edit the story. The article also describes a case study that applies the concepts described practically.

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Publication Details

Journal
Journal of the Association for Information Science and Technology
Published
2025-11-13
DOI
https://doi.org/10.1002/asi.70036
Primary Topic
Data Visualization and Analytics
Type
article
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article

Using generative AI to co‐design data‐driven stories

Angelica Lo Duca
Journal of the Association for Information Science and Technology
Data Visualization and Analytics
article

Using generative AI to co‐design data‐driven stories

Angelica Lo Duca
article en

Abstract

Abstract Data storytelling combines communication and visualization techniques with storytelling principles to convey insights meaningfully and engagingly. This paper introduces the AI‐DIKW framework, an extension of the Story Data–Information–Knowledge–Wisdom (S‐DIKW) hierarchy, designed to support the co‐creation of data‐driven stories by combining human expertise with Generative AI. The AI‐DIKW framework extends the S‐DIKW model through the application of the journalistic 5‐Ws, which guide Generative AI to provide consistent and contextually relevant outputs. This study describes how Generative AI can contribute to the iterative construction of a story's key components while ensuring alignment with ethical principles. Applying Generative AI at the AI‐Data stage involves extracting insights from the data. Applying Generative AI at the AI‐Information stage means enriching the insight with relevant context, while at the AI‐Knowledge stage, Generative AI helps the data storyteller to enrich the story with meaningful next steps, anchored to a selected ethical framework. Finally, at the AI‐Wisdom stage, Generative AI helps the data storyteller to tailor the story to specific audiences. At each stage of the AI‐DIKW framework, Generative AI acts as a co‐designer that helps the data storyteller to frame and edit the story. The article also describes a case study that applies the concepts described practically.

Journal of the Association for Information Science and TechnologyVol. 76(13)
Institute of Informatics and Telematics (IT), National Research Council (IT)
Openalex Percentile: Top 65%
Data Visualization and Analytics
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Using generative <scp>AI</scp> to co‐design data‐driven stories — Angelica Lo Duca · Journal of the Association for Information Science and Technology (2025) | TGRS Research Map | TGRS