Visual Analytics (VA) supports iterative exploration and insight discovery, but current frameworks lack sufficient provenance management to capture the sequence of analytical actions and reasoning. This limitation hinders the reconstruction of analytical processes and the generation of coherent narratives. We propose the VASTorytelling Framework, which extends existing VA framework by incorporating mechanisms for recording user interactions, annotating visualizations, and utilizing extended data -— including logs and external knowledge -— for narrative construction. The framework supports metacognitive reflection and integrates large language models to assist narrative generation and reduce cognitive load. This approach enhances traceability, explainability, and communication in long-term VA activities.
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