DATA-DRIVEN STORYTELLING APPROACHES FOR ENHANCING THE NARRATIVE DEPTH OF DIGITAL VISUAL ARTWORKS

Anshul Srivastava; Surbhi Saraswat; Kapil Mundada; Yang Lu; Dimple Bahri; M. Abirami

doi:10.29121/shodhkosh.v7.i4s.2026.7488

Authors

Anshul Srivastava Assistant Professor, Amity International Business School, Amity University, Noida, India
Dr. Surbhi Saraswat Professor, Amity Institute of English Studies and Research, Amity University, Noida, India
Kapil Mundada Associate Professor, Department of Instrumentation and Control Engineering, Vishwakarma Institute of Technology, Pune, Maharashtra 411037, India
Yang Lu Faculty of Education, Shinawatra University, Bang Toei, Thailand
Dimple Bahri Assistant Professor, Department of Civil Engineering, Faculty of Engineering and Technology, JAIN (Deemed-to-be University), Bengaluru, Karnataka, India
Dr. M. Abirami M. Tech, Ph.D., Assistant Professor, Department of Computer Science and Engineering, Panimalar Engineering College, Tamil Nadu, India

DOI:

https://doi.org/10.29121/shodhkosh.v7.i4s.2026.7488

Keywords:

Data-Driven Storytelling, Digital Visual Art, Narrative Depth, Data Visualization, Artificial Intelligence in Art, Interactive Art, Generative Art, Visual Narratives

Abstract [English]

The active evolution of digital technologies has impacted the contemporary visual art colossally, as it has provided the possibility of creating new approaches to the narration of stories based on the combination of data, artificial intelligence, and the interactive technology. This essay provides an argument about the idea of data-driven storytelling as the means of enriching the narrative content of the digital visual images. It also examines the way in which the structured and the unstructured data can be turned into meaningful visual stories beyond the more traditional and non-evolving representations. The article unveils some of the biggest hindrances to the process of filling the gap between data analysis and the representation of this information in art, in particular, the coherence, emotional appeal and interpretability. To deal with these, a conceptual model is proposed which brings in five basic components viz. data acquisition, data processing and analysis, narrative construction, visual representation and user interaction. The form of integrating computing techniques and design is the way of arriving at a prototype system, depicting dynamic and interactive story telling. The analogy to the traditional visual art narrates about the advantages of the provided strategy in the framework of the richness of the stories, malleability, interactivity, and engagement of the users. These findings could indicate that data-driven narratives can be used to generate multi-layered and non-linear narratives that can be updated with real-time data and user feedback to generate more immersive and context-aware art experiences. The future directions which might be considered by the study are also touched upon like the use of immersive technologies and ethical concerns on the use of data. In general, this research contributes in some way to the future of digital art practices in that it provides a systematic approach of incorporating information and storytelling to enhance the impact of the story.

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