Using the S‐<scp>DIKW</scp> framework to transform data visualization into data storytelling

Abstract Communicating insights from data effectively requires design skills, technical knowledge, and experience. Data must be accurately represented with aesthetically pleasing visuals and engaging text to effectively communicate to the intended audience. Data storytelling has received much attention lately, but as of yet, it does not have a theoretical and practical foundation in information science. A data story adds context, narrative, and structure to the visual representation of data, providing audiences with character, plot, and a holistic experience of narrative. This paper proposes a methodological approach to transform a data visualization into a data story based on the Data‐Information‐Knowledge‐Wisdom (DIKW) pyramid and the S‐DIKW Framework. Starting from the bottom of the pyramid, the proposed approach defines a strategy to represent insights extracted from data. Data is then turned into information by identifying character(s) facing a problem, adding textual and graphic content; information is turned into knowledge by organizing what happens as a plot. Finally, a call to wise action—always informed by cultural and community values—completes the storytelling transformation to create a data story. This article contributes to the theoretical understanding of data stories as emerging information forms, supporting richer understandings of a story as information in the information sciences.

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Publication Details

Journal
Journal of the Association for Information Science and Technology
Published
2024-12-24
DOI
https://doi.org/10.1002/asi.24973
Citations
6
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
1.50
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article

Using the S‐DIKW framework to transform data visualization into data storytelling

Kate McDowell, Angelica Lo Duca
6 citations
Journal of the Association for Information Science and Technology
Data Visualization and Analytics
1.50
article

Using the S‐DIKW framework to transform data visualization into data storytelling

Kate McDowell, Angelica Lo Duca
article en
6 citations

Abstract

Abstract Communicating insights from data effectively requires design skills, technical knowledge, and experience. Data must be accurately represented with aesthetically pleasing visuals and engaging text to effectively communicate to the intended audience. Data storytelling has received much attention lately, but as of yet, it does not have a theoretical and practical foundation in information science. A data story adds context, narrative, and structure to the visual representation of data, providing audiences with character, plot, and a holistic experience of narrative. This paper proposes a methodological approach to transform a data visualization into a data story based on the Data‐Information‐Knowledge‐Wisdom (DIKW) pyramid and the S‐DIKW Framework. Starting from the bottom of the pyramid, the proposed approach defines a strategy to represent insights extracted from data. Data is then turned into information by identifying character(s) facing a problem, adding textual and graphic content; information is turned into knowledge by organizing what happens as a plot. Finally, a call to wise action—always informed by cultural and community values—completes the storytelling transformation to create a data story. This article contributes to the theoretical understanding of data stories as emerging information forms, supporting richer understandings of a story as information in the information sciences.

Journal of the Association for Information Science and TechnologyVol. 76(5)
University of Illinois Urbana-Champaign (US), Institute of Informatics and Telematics (IT), National Research Council (IT)
Quality Education
Openalex Percentile: Top 16%
Data Visualization and Analytics
1.50
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Using the S‐<scp>DIKW</scp> framework to transform data visualization into data storytelling — Kate McDowell, Angelica Lo Duca · Journal of the Association for Information Science and Technology (2024) | TGRS Research Map | TGRS