Data Storytelling Method:Extraction,Reorganization and Narrative
[Purpose/Significance]The data-driven era faces many challenges such as difficulties in data cognition,obscure interpretation results,and insufficient credibility of model decision-making.The data sto-rytelling method that integrates interpretable results provides theoretical support and solutions to address the challenges and enhance the value of data utilization.[Method/Process]This paper summarizes the interpre-tation form of model-agnostic local interpretability technology,the narrative structure of data stories and the methods used in the current research on data storytelling.Based on the interpretability theory and the realiza-tion mode of data storytelling,a data storytelling model of"extraction-reorganization-narrative"is construct-ed,and the data story mapping process is given by using the defined element tuple.The key techniques of story model design are introduced briefly.[Result/Conclusion]Based on the theory of data storytelling model design,this paper proposes a"fan-shaped"storytelling implementation path for interpretation results and an interactive framework that integrates the elements of interpretation results and storytelling model,and reflects the practical value of data storytelling method in result interpretation through case studies.A framework of data storytelling methods based on interpretable results is constructed,which provides new ideas for expand-ing storytelling paths with data perception and cognition and assisting intelligent decision-making.
data storytellinginterpretabilitymodel-agnosticlocal interpretabilitynarrative
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