journal article Open Access Jul 25, 2025

VisRep: Towards an Automated, Reflective AI System for Documenting Visualisation Design Processes

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Abstract
VisRep (Visualisation Report) is an AI-powered system for capturing and structuring the early stages of the visualisation design process. It addresses a critical gap in predesign: the lack of tools that can naturally record, organise, and transform raw ideation, spoken thoughts, sketches, and evolving concepts into polished, shareable outputs. Users engage in talk-aloud sessions through a terminal-style interface supported by intelligent transcription and eleven structured questions that frame intent, audience, and output goals. These inputs are then processed by a large language model (LLM) guided by markdown-based output templates for reports, posters, and slides. The system aligns free-form ideas with structured communication using prompt engineering to ensure clarity, coherence, and visual consistency. VisRep not only automates the generation of professional deliverables but also enhances reflective practice by bridging spontaneous ideation and structured documentation. This paper introduces VisRep’s methodology, interface design, and AI-driven workflow, demonstrating how it improves the fidelity and transparency of the visualisation design process across academic, professional, and creative domains.
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Published
Jul 25, 2025
Vol/Issue
7(3)
Pages
72
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Cite This Article
Aron E. Owen, Jonathan C. Roberts (2025). VisRep: Towards an Automated, Reflective AI System for Documenting Visualisation Design Processes. Machine Learning and Knowledge Extraction, 7(3), 72. https://doi.org/10.3390/make7030072
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